Evaluation of Hierarchical Clustering Algorithms for Document Datasets

DTIC Science & Technology

2002-06-03

link, complete-link, and group average ( UPGMA )) and a new set of merging criteria derived from the six partitional criterion functions. Overall, we...used the single-link, complete-link, and UPGMA schemes, as well as, the various partitional criterion functions described in Section 3.1. The single-link...other (complete-link approach). The UPGMA scheme [16] (also known as group average) overcomes these problems by measuring the similarity of two clusters

On the star partition dimension of comb product of cycle and complete graph

NASA Astrophysics Data System (ADS)

Alfarisi, Ridho; Darmaji; Dafik

2017-06-01

Let G = (V, E) be a connected graphs with vertex set V (G), edge set E(G) and S ⊆ V (G). For an ordered partition Π = {S 1, S 2, S 3, …, Sk } of V (G), the representation of a vertex v ∈ V (G) with respect to Π is the k-vectors r(v|Π) = (d(v, S 1), d(v, S 2), …, d(v, Sk )), where d(v, Sk ) represents the distance between the vertex v and the set Sk , defined by d(v, Sk ) = min{d(v, x)|x ∈ Sk}. The partition Π of V (G) is a resolving partition if the k-vektors r(v|Π), v ∈ V (G) are distinct. The minimum resolving partition Π is a partition dimension of G, denoted by pd(G). The resolving partition Π = {S 1, S 2, S 3, …, Sk} is called a star resolving partition for G if it is a resolving partition and each subgraph induced by Si , 1 ≤ i ≤ k, is a star. The minimum k for which there exists a star resolving partition of V (G) is the star partition dimension of G, denoted by spd(G). Finding a star partition dimension of G is classified to be a NP-Hard problem. Furthermore, the comb product between G and H, denoted by G ⊲ H, is a graph obtained by taking one copy of G and |V (G)| copies of H and grafting the i-th copy of H at the vertex o to the i-th vertex of G. By definition of comb product, we can say that V (G ⊲ H) = {(a, u)|a ∈ V (G), u ∈ V (H)} and (a, u)(b, v) ∈ E(G ⊲ H) whenever a = b and uv ∈ E(H), or ab ∈ E(G) and u = v = o. In this paper, we will study the star partition dimension of comb product of cycle and complete graph, namely Cn ⊲ Km and Km ⊲ Cn for n ≥ 3 and m ≥ 3.

Decision tree modeling using R.

PubMed

Zhang, Zhongheng

2016-08-01

In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.

The threshold bootstrap clustering: a new approach to find families or transmission clusters within molecular quasispecies.

PubMed

Prosperi, Mattia C F; De Luca, Andrea; Di Giambenedetto, Simona; Bracciale, Laura; Fabbiani, Massimiliano; Cauda, Roberto; Salemi, Marco

2010-10-25

Phylogenetic methods produce hierarchies of molecular species, inferring knowledge about taxonomy and evolution. However, there is not yet a consensus methodology that provides a crisp partition of taxa, desirable when considering the problem of intra/inter-patient quasispecies classification or infection transmission event identification. We introduce the threshold bootstrap clustering (TBC), a new methodology for partitioning molecular sequences, that does not require a phylogenetic tree estimation. The TBC is an incremental partition algorithm, inspired by the stochastic Chinese restaurant process, and takes advantage of resampling techniques and models of sequence evolution. TBC uses as input a multiple alignment of molecular sequences and its output is a crisp partition of the taxa into an automatically determined number of clusters. By varying initial conditions, the algorithm can produce different partitions. We describe a procedure that selects a prime partition among a set of candidate ones and calculates a measure of cluster reliability. TBC was successfully tested for the identification of type-1 human immunodeficiency and hepatitis C virus subtypes, and compared with previously established methodologies. It was also evaluated in the problem of HIV-1 intra-patient quasispecies clustering, and for transmission cluster identification, using a set of sequences from patients with known transmission event histories. TBC has been shown to be effective for the subtyping of HIV and HCV, and for identifying intra-patient quasispecies. To some extent, the algorithm was able also to infer clusters corresponding to events of infection transmission. The computational complexity of TBC is quadratic in the number of taxa, lower than other established methods; in addition, TBC has been enhanced with a measure of cluster reliability. The TBC can be useful to characterise molecular quasipecies in a broad context.

Optimal Partitioning of a Surveillance Space for Persistent Coverage Using Multiple Autonomous Unmanned Aerial Vehicles: An Integer Programming Approach

DTIC Science & Technology

2014-03-27

asymptotically equal. Carlsson shows that the problem is solved by treating each subregion Ri as a traveling salesman problem (TSP) with a set of points that...terminal state to the goal. If no- travel zones are repre- sented as the union of regions Akx > Bk, the coverage problem can be expressed as an IP [14...3 1.2 Problem Statement

Dynamics of Quantum Adiabatic Evolution Algorithm for Number Partitioning

NASA Technical Reports Server (NTRS)

Smelyanskiy, V. N.; Toussaint, U. V.; Timucin, D. A.

2002-01-01

We have developed a general technique to study the dynamics of the quantum adiabatic evolution algorithm applied to random combinatorial optimization problems in the asymptotic limit of large problem size n. We use as an example the NP-complete Number Partitioning problem and map the algorithm dynamics to that of an auxiliary quantum spin glass system with the slowly varying Hamiltonian. We use a Green function method to obtain the adiabatic eigenstates and the minimum excitation gap. g min, = O(n 2(exp -n/2), corresponding to the exponential complexity of the algorithm for Number Partitioning. The key element of the analysis is the conditional energy distribution computed for the set of all spin configurations generated from a given (ancestor) configuration by simultaneous flipping of a fixed number of spins. For the problem in question this distribution is shown to depend on the ancestor spin configuration only via a certain parameter related to 'the energy of the configuration. As the result, the algorithm dynamics can be described in terms of one-dimensional quantum diffusion in the energy space. This effect provides a general limitation of a quantum adiabatic computation in random optimization problems. Analytical results are in agreement with the numerical simulation of the algorithm.

Dynamics of Quantum Adiabatic Evolution Algorithm for Number Partitioning

NASA Technical Reports Server (NTRS)

Smelyanskiy, Vadius; vonToussaint, Udo V.; Timucin, Dogan A.; Clancy, Daniel (Technical Monitor)

2002-01-01

We have developed a general technique to study the dynamics of the quantum adiabatic evolution algorithm applied to random combinatorial optimization problems in the asymptotic limit of large problem size n. We use as an example the NP-complete Number Partitioning problem and map the algorithm dynamics to that of an auxiliary quantum spin glass system with the slowly varying Hamiltonian. We use a Green function method to obtain the adiabatic eigenstates and the minimum exitation gap, gmin = O(n2(sup -n/2)), corresponding to the exponential complexity of the algorithm for Number Partitioning. The key element of the analysis is the conditional energy distribution computed for the set of all spin configurations generated from a given (ancestor) configuration by simultaneous flipping of a fixed number of spins. For the problem in question this distribution is shown to depend on the ancestor spin configuration only via a certain parameter related to the energy of the configuration. As the result, the algorithm dynamics can be described in terms of one-dimensional quantum diffusion in the energy space. This effect provides a general limitation of a quantum adiabatic computation in random optimization problems. Analytical results are in agreement with the numerical simulation of the algorithm.

A Fifth-order Symplectic Trigonometrically Fitted Partitioned Runge-Kutta Method

NASA Astrophysics Data System (ADS)

Kalogiratou, Z.; Monovasilis, Th.; Simos, T. E.

2007-09-01

Trigonometrically fitted symplectic Partitioned Runge Kutta (EFSPRK) methods for the numerical integration of Hamoltonian systems with oscillatory solutions are derived. These methods integrate exactly differential systems whose solutions can be expressed as linear combinations of the set of functions sin(wx),cos(wx), w∈R. We modify a fifth order symplectic PRK method with six stages so to derive an exponentially fitted SPRK method. The methods are tested on the numerical integration of the two body problem.

Methods of Conceptual Clustering and their Relation to Numerical Taxonomy.

DTIC Science & Technology

1985-07-22

the conceptual clustering problem is to first solve theaggregation problem, and then the characterization problem. In machine learning, the...cluster- ings by first generating some number of possible clusterings. For each clustering generated, one calls a learning from examples subroutine, which...class 1 from class 2, and vice versa, only the first combination implies a partition over the set of theoretically possible objects. The first

Identifying finite-time coherent sets from limited quantities of Lagrangian data.

PubMed

Williams, Matthew O; Rypina, Irina I; Rowley, Clarence W

2015-08-01

A data-driven procedure for identifying the dominant transport barriers in a time-varying flow from limited quantities of Lagrangian data is presented. Our approach partitions state space into coherent pairs, which are sets of initial conditions chosen to minimize the number of trajectories that "leak" from one set to the other under the influence of a stochastic flow field during a pre-specified interval in time. In practice, this partition is computed by solving an optimization problem to obtain a pair of functions whose signs determine set membership. From prior experience with synthetic, "data rich" test problems, and conceptually related methods based on approximations of the Perron-Frobenius operator, we observe that the functions of interest typically appear to be smooth. We exploit this property by using the basis sets associated with spectral or "mesh-free" methods, and as a result, our approach has the potential to more accurately approximate these functions given a fixed amount of data. In practice, this could enable better approximations of the coherent pairs in problems with relatively limited quantities of Lagrangian data, which is usually the case with experimental geophysical data. We apply this method to three examples of increasing complexity: The first is the double gyre, the second is the Bickley Jet, and the third is data from numerically simulated drifters in the Sulu Sea.

Identifying finite-time coherent sets from limited quantities of Lagrangian data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Matthew O.; Rypina, Irina I.; Rowley, Clarence W.

A data-driven procedure for identifying the dominant transport barriers in a time-varying flow from limited quantities of Lagrangian data is presented. Our approach partitions state space into coherent pairs, which are sets of initial conditions chosen to minimize the number of trajectories that “leak” from one set to the other under the influence of a stochastic flow field during a pre-specified interval in time. In practice, this partition is computed by solving an optimization problem to obtain a pair of functions whose signs determine set membership. From prior experience with synthetic, “data rich” test problems, and conceptually related methods basedmore » on approximations of the Perron-Frobenius operator, we observe that the functions of interest typically appear to be smooth. We exploit this property by using the basis sets associated with spectral or “mesh-free” methods, and as a result, our approach has the potential to more accurately approximate these functions given a fixed amount of data. In practice, this could enable better approximations of the coherent pairs in problems with relatively limited quantities of Lagrangian data, which is usually the case with experimental geophysical data. We apply this method to three examples of increasing complexity: The first is the double gyre, the second is the Bickley Jet, and the third is data from numerically simulated drifters in the Sulu Sea.« less

Stencils and problem partitionings: Their influence on the performance of multiple processor systems

NASA Technical Reports Server (NTRS)

Reed, D. A.; Adams, L. M.; Patrick, M. L.

1986-01-01

Given a discretization stencil, partitioning the problem domain is an important first step for the efficient solution of partial differential equations on multiple processor systems. Partitions are derived that minimize interprocessor communication when the number of processors is known a priori and each domain partition is assigned to a different processor. This partitioning technique uses the stencil structure to select appropriate partition shapes. For square problem domains, it is shown that non-standard partitions (e.g., hexagons) are frequently preferable to the standard square partitions for a variety of commonly used stencils. This investigation is concluded with a formalization of the relationship between partition shape, stencil structure, and architecture, allowing selection of optimal partitions for a variety of parallel systems.

Partitioning and packing mathematical simulation models for calculation on parallel computers

NASA Technical Reports Server (NTRS)

Arpasi, D. J.; Milner, E. J.

1986-01-01

The development of multiprocessor simulations from a serial set of ordinary differential equations describing a physical system is described. Degrees of parallelism (i.e., coupling between the equations) and their impact on parallel processing are discussed. The problem of identifying computational parallelism within sets of closely coupled equations that require the exchange of current values of variables is described. A technique is presented for identifying this parallelism and for partitioning the equations for parallel solution on a multiprocessor. An algorithm which packs the equations into a minimum number of processors is also described. The results of the packing algorithm when applied to a turbojet engine model are presented in terms of processor utilization.

Minimum nonuniform graph partitioning with unrelated weights

NASA Astrophysics Data System (ADS)

Makarychev, K. S.; Makarychev, Yu S.

2017-12-01

We give a bi-criteria approximation algorithm for the Minimum Nonuniform Graph Partitioning problem, recently introduced by Krauthgamer, Naor, Schwartz and Talwar. In this problem, we are given a graph G=(V,E) and k numbers ρ_1,\\dots, ρ_k. The goal is to partition V into k disjoint sets (bins) P_1,\\dots, P_k satisfying \\vert P_i\\vert≤ ρi \\vert V\\vert for all i, so as to minimize the number of edges cut by the partition. Our bi-criteria algorithm gives an O(\\sqrt{log \\vert V\\vert log k}) approximation for the objective function in general graphs and an O(1) approximation in graphs excluding a fixed minor. The approximate solution satisfies the relaxed capacity constraints \\vert P_i\\vert ≤ (5+ \\varepsilon)ρi \\vert V\\vert. This algorithm is an improvement upon the O(log \\vert V\\vert)-approximation algorithm by Krauthgamer, Naor, Schwartz and Talwar. We extend our results to the case of 'unrelated weights' and to the case of 'unrelated d-dimensional weights'. A preliminary version of this work was presented at the 41st International Colloquium on Automata, Languages and Programming (ICALP 2014). Bibliography: 7 titles.

Efficient bulk-loading of gridfiles

NASA Technical Reports Server (NTRS)

Leutenegger, Scott T.; Nicol, David M.

1994-01-01

This paper considers the problem of bulk-loading large data sets for the gridfile multiattribute indexing technique. We propose a rectilinear partitioning algorithm that heuristically seeks to minimize the size of the gridfile needed to ensure no bucket overflows. Empirical studies on both synthetic data sets and on data sets drawn from computational fluid dynamics applications demonstrate that our algorithm is very efficient, and is able to handle large data sets. In addition, we present an algorithm for bulk-loading data sets too large to fit in main memory. Utilizing a sort of the entire data set it creates a gridfile without incurring any overflows.

Parameterized Complexity Results for General Factors in Bipartite Graphs with an Application to Constraint Programming

NASA Astrophysics Data System (ADS)

Gutin, Gregory; Kim, Eun Jung; Soleimanfallah, Arezou; Szeider, Stefan; Yeo, Anders

The NP-hard general factor problem asks, given a graph and for each vertex a list of integers, whether the graph has a spanning subgraph where each vertex has a degree that belongs to its assigned list. The problem remains NP-hard even if the given graph is bipartite with partition U ⊎ V, and each vertex in U is assigned the list {1}; this subproblem appears in the context of constraint programming as the consistency problem for the extended global cardinality constraint. We show that this subproblem is fixed-parameter tractable when parameterized by the size of the second partite set V. More generally, we show that the general factor problem for bipartite graphs, parameterized by |V |, is fixed-parameter tractable as long as all vertices in U are assigned lists of length 1, but becomes W[1]-hard if vertices in U are assigned lists of length at most 2. We establish fixed-parameter tractability by reducing the problem instance to a bounded number of acyclic instances, each of which can be solved in polynomial time by dynamic programming.

Integrated data lookup and replication scheme in mobile ad hoc networks

NASA Astrophysics Data System (ADS)

Chen, Kai; Nahrstedt, Klara

2001-11-01

Accessing remote data is a challenging task in mobile ad hoc networks. Two problems have to be solved: (1) how to learn about available data in the network; and (2) how to access desired data even when the original copy of the data is unreachable. In this paper, we develop an integrated data lookup and replication scheme to solve these problems. In our scheme, a group of mobile nodes collectively host a set of data to improve data accessibility for all members of the group. They exchange data availability information by broadcasting advertising (ad) messages to the group using an adaptive sending rate policy. The ad messages are used by other nodes to derive a local data lookup table, and to reduce data redundancy within a connected group. Our data replication scheme predicts group partitioning based on each node's current location and movement patterns, and replicates data to other partitions before partitioning occurs. Our simulations show that data availability information can quickly propagate throughout the network, and that the successful data access ratio of each node is significantly improved.

A comparison of latent class, K-means, and K-median methods for clustering dichotomous data.

PubMed

Brusco, Michael J; Shireman, Emilie; Steinley, Douglas

2017-09-01

The problem of partitioning a collection of objects based on their measurements on a set of dichotomous variables is a well-established problem in psychological research, with applications including clinical diagnosis, educational testing, cognitive categorization, and choice analysis. Latent class analysis and K-means clustering are popular methods for partitioning objects based on dichotomous measures in the psychological literature. The K-median clustering method has recently been touted as a potentially useful tool for psychological data and might be preferable to its close neighbor, K-means, when the variable measures are dichotomous. We conducted simulation-based comparisons of the latent class, K-means, and K-median approaches for partitioning dichotomous data. Although all 3 methods proved capable of recovering cluster structure, K-median clustering yielded the best average performance, followed closely by latent class analysis. We also report results for the 3 methods within the context of an application to transitive reasoning data, in which it was found that the 3 approaches can exhibit profound differences when applied to real data. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A partitioning strategy for nonuniform problems on multiprocessors

NASA Technical Reports Server (NTRS)

Berger, M. J.; Bokhari, S.

1985-01-01

The partitioning of a problem on a domain with unequal work estimates in different subddomains is considered in a way that balances the work load across multiple processors. Such a problem arises for example in solving partial differential equations using an adaptive method that places extra grid points in certain subregions of the domain. A binary decomposition of the domain is used to partition it into rectangles requiring equal computational effort. The communication costs of mapping this partitioning onto different microprocessors: a mesh-connected array, a tree machine and a hypercube is then studied. The communication cost expressions can be used to determine the optimal depth of the above partitioning.

Optimal Partitioning of a Data Set Based on the "p"-Median Model

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich

2008-01-01

Although the "K"-means algorithm for minimizing the within-cluster sums of squared deviations from cluster centroids is perhaps the most common method for applied cluster analyses, a variety of other criteria are available. The "p"-median model is an especially well-studied clustering problem that requires the selection of "p" objects to serve as…

Joint Optimization of Receiver Placement and Illuminator Selection for a Multiband Passive Radar Network.

PubMed

Xie, Rui; Wan, Xianrong; Hong, Sheng; Yi, Jianxin

2017-06-14

The performance of a passive radar network can be greatly improved by an optimal radar network structure. Generally, radar network structure optimization consists of two aspects, namely the placement of receivers in suitable places and selection of appropriate illuminators. The present study investigates issues concerning the joint optimization of receiver placement and illuminator selection for a passive radar network. Firstly, the required radar cross section (RCS) for target detection is chosen as the performance metric, and the joint optimization model boils down to the partition p -center problem (PPCP). The PPCP is then solved by a proposed bisection algorithm. The key of the bisection algorithm lies in solving the partition set covering problem (PSCP), which can be solved by a hybrid algorithm developed by coupling the convex optimization with the greedy dropping algorithm. In the end, the performance of the proposed algorithm is validated via numerical simulations.

A Combined Adaptive Tabu Search and Set Partitioning Approach for the Crew Scheduling Problem with an Air Tanker Crew Application

DTIC Science & Technology

2002-08-15

Agency Name(s) and Address(es) Maj Juan Vasquez AFOSR/NM 801 N. Randolph St., Rm 732 Arlington, VA 22203-1977 Sponsor/Monitor’s Acronym(s) Sponsor... Gelman , E., Patty, B., and R. Tanga. 1991. Recent Advances in Crew-Pairing Optimization at American Airlines, Interfaces, 21(1):62-74. Baker, E.K...Operations Research, 25(11):887-894. Chu, H.D., Gelman , E., and E.L. Johnson. 1997. Solving Large Scale Crew Scheduling Problems, European

Graph Partitioning for Parallel Applications in Heterogeneous Grid Environments

NASA Technical Reports Server (NTRS)

Bisws, Rupak; Kumar, Shailendra; Das, Sajal K.; Biegel, Bryan (Technical Monitor)

2002-01-01

The problem of partitioning irregular graphs and meshes for parallel computations on homogeneous systems has been extensively studied. However, these partitioning schemes fail when the target system architecture exhibits heterogeneity in resource characteristics. With the emergence of technologies such as the Grid, it is imperative to study the partitioning problem taking into consideration the differing capabilities of such distributed heterogeneous systems. In our model, the heterogeneous system consists of processors with varying processing power and an underlying non-uniform communication network. We present in this paper a novel multilevel partitioning scheme for irregular graphs and meshes, that takes into account issues pertinent to Grid computing environments. Our partitioning algorithm, called MiniMax, generates and maps partitions onto a heterogeneous system with the objective of minimizing the maximum execution time of the parallel distributed application. For experimental performance study, we have considered both a realistic mesh problem from NASA as well as synthetic workloads. Simulation results demonstrate that MiniMax generates high quality partitions for various classes of applications targeted for parallel execution in a distributed heterogeneous environment.

A Study of Energy Partitioning Using A Set of Related Explosive Formulations

NASA Astrophysics Data System (ADS)

Lieber, Mark; Foster, Joseph C., Jr.; Stewart, D. Scott

2011-06-01

Condensed phase high explosives convert potential energy stored in the electro-magnetic field structure of complex molecules to kinetic energy during the detonation process. This energy is manifest in the internal thermodynamic energy and the translational flow of the products. Historically, the explosive design problem has focused on intramolecular stoichiometry providing prompt reactions based on transport physics at the molecular scale. Modern material design has evolved to approaches that employee intermolecular ingredients to alter the spatial and temporal distribution of energy release. CHEETA has been used to produce data for a set of fictitious explosive formulations based on C-4 to study the partitioning of the available energy between internal and flow energy in the detonation. The equation of state information from CHEETA has been used in ALE3D to develop an understanding of the relationship between variations in the formulation parameters and the internal energy cycle in the products.

Using Optimisation Techniques to Granulise Rough Set Partitions

NASA Astrophysics Data System (ADS)

Crossingham, Bodie; Marwala, Tshilidzi

2007-11-01

This paper presents an approach to optimise rough set partition sizes using various optimisation techniques. Three optimisation techniques are implemented to perform the granularisation process, namely, genetic algorithm (GA), hill climbing (HC) and simulated annealing (SA). These optimisation methods maximise the classification accuracy of the rough sets. The proposed rough set partition method is tested on a set of demographic properties of individuals obtained from the South African antenatal survey. The three techniques are compared in terms of their computational time, accuracy and number of rules produced when applied to the Human Immunodeficiency Virus (HIV) data set. The optimised methods results are compared to a well known non-optimised discretisation method, equal-width-bin partitioning (EWB). The accuracies achieved after optimising the partitions using GA, HC and SA are 66.89%, 65.84% and 65.48% respectively, compared to the accuracy of EWB of 59.86%. In addition to rough sets providing the plausabilities of the estimated HIV status, they also provide the linguistic rules describing how the demographic parameters drive the risk of HIV.

Partitioning problems in parallel, pipelined and distributed computing

NASA Technical Reports Server (NTRS)

Bokhari, S.

1985-01-01

The problem of optimally assigning the modules of a parallel program over the processors of a multiple computer system is addressed. A Sum-Bottleneck path algorithm is developed that permits the efficient solution of many variants of this problem under some constraints on the structure of the partitions. In particular, the following problems are solved optimally for a single-host, multiple satellite system: partitioning multiple chain structured parallel programs, multiple arbitrarily structured serial programs and single tree structured parallel programs. In addition, the problems of partitioning chain structured parallel programs across chain connected systems and across shared memory (or shared bus) systems are also solved under certain constraints. All solutions for parallel programs are equally applicable to pipelined programs. These results extend prior research in this area by explicitly taking concurrency into account and permit the efficient utilization of multiple computer architectures for a wide range of problems of practical interest.

Partitioning in parallel processing of production systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oflazer, K.

1987-01-01

This thesis presents research on certain issues related to parallel processing of production systems. It first presents a parallel production system interpreter that has been implemented on a four-processor multiprocessor. This parallel interpreter is based on Forgy's OPS5 interpreter and exploits production-level parallelism in production systems. Runs on the multiprocessor system indicate that it is possible to obtain speed-up of around 1.7 in the match computation for certain production systems when productions are split into three sets that are processed in parallel. The next issue addressed is that of partitioning a set of rules to processors in a parallel interpretermore » with production-level parallelism, and the extent of additional improvement in performance. The partitioning problem is formulated and an algorithm for approximate solutions is presented. The thesis next presents a parallel processing scheme for OPS5 production systems that allows some redundancy in the match computation. This redundancy enables the processing of a production to be divided into units of medium granularity each of which can be processed in parallel. Subsequently, a parallel processor architecture for implementing the parallel processing algorithm is presented.« less

ESTimating plant phylogeny: lessons from partitioning

PubMed Central

de la Torre, Jose EB; Egan, Mary G; Katari, Manpreet S; Brenner, Eric D; Stevenson, Dennis W; Coruzzi, Gloria M; DeSalle, Rob

2006-01-01

Background While Expressed Sequence Tags (ESTs) have proven a viable and efficient way to sample genomes, particularly those for which whole-genome sequencing is impractical, phylogenetic analysis using ESTs remains difficult. Sequencing errors and orthology determination are the major problems when using ESTs as a source of characters for systematics. Here we develop methods to incorporate EST sequence information in a simultaneous analysis framework to address controversial phylogenetic questions regarding the relationships among the major groups of seed plants. We use an automated, phylogenetically derived approach to orthology determination called OrthologID generate a phylogeny based on 43 process partitions, many of which are derived from ESTs, and examine several measures of support to assess the utility of EST data for phylogenies. Results A maximum parsimony (MP) analysis resulted in a single tree with relatively high support at all nodes in the tree despite rampant conflict among trees generated from the separate analysis of individual partitions. In a comparison of broader-scale groupings based on cellular compartment (ie: chloroplast, mitochondrial or nuclear) or function, only the nuclear partition tree (based largely on EST data) was found to be topologically identical to the tree based on the simultaneous analysis of all data. Despite topological conflict among the broader-scale groupings examined, only the tree based on morphological data showed statistically significant differences. Conclusion Based on the amount of character support contributed by EST data which make up a majority of the nuclear data set, and the lack of conflict of the nuclear data set with the simultaneous analysis tree, we conclude that the inclusion of EST data does provide a viable and efficient approach to address phylogenetic questions within a parsimony framework on a genomic scale, if problems of orthology determination and potential sequencing errors can be overcome. In addition, approaches that examine conflict and support in a simultaneous analysis framework allow for a more precise understanding of the evolutionary history of individual process partitions and may be a novel way to understand functional aspects of different kinds of cellular classes of gene products. PMID:16776834

Spatial coding-based approach for partitioning big spatial data in Hadoop

NASA Astrophysics Data System (ADS)

Yao, Xiaochuang; Mokbel, Mohamed F.; Alarabi, Louai; Eldawy, Ahmed; Yang, Jianyu; Yun, Wenju; Li, Lin; Ye, Sijing; Zhu, Dehai

2017-09-01

Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.

A local search for a graph clustering problem

NASA Astrophysics Data System (ADS)

Navrotskaya, Anna; Il'ev, Victor

2016-10-01

In the clustering problems one has to partition a given set of objects (a data set) into some subsets (called clusters) taking into consideration only similarity of the objects. One of most visual formalizations of clustering is graph clustering, that is grouping the vertices of a graph into clusters taking into consideration the edge structure of the graph whose vertices are objects and edges represent similarities between the objects. In the graph k-clustering problem the number of clusters does not exceed k and the goal is to minimize the number of edges between clusters and the number of missing edges within clusters. This problem is NP-hard for any k ≥ 2. We propose a polynomial time (2k-1)-approximation algorithm for graph k-clustering. Then we apply a local search procedure to the feasible solution found by this algorithm and hold experimental research of obtained heuristics.

Dominant partition method. [based on a wave function formalism

NASA Technical Reports Server (NTRS)

Dixon, R. M.; Redish, E. F.

1979-01-01

By use of the L'Huillier, Redish, and Tandy (LRT) wave function formalism, a partially connected method, the dominant partition method (DPM) is developed for obtaining few body reductions of the many body problem in the LRT and Bencze, Redish, and Sloan (BRS) formalisms. The DPM maps the many body problem to a fewer body one by using the criterion that the truncated formalism must be such that consistency with the full Schroedinger equation is preserved. The DPM is based on a class of new forms for the irreducible cluster potential, which is introduced in the LRT formalism. Connectivity is maintained with respect to all partitions containing a given partition, which is referred to as the dominant partition. Degrees of freedom corresponding to the breakup of one or more of the clusters of the dominant partition are treated in a disconnected manner. This approach for simplifying the complicated BRS equations is appropriate for physical problems where a few body reaction mechanism prevails.

Mesh-free data transfer algorithms for partitioned multiphysics problems: Conservation, accuracy, and parallelism

DOE PAGES

Slattery, Stuart R.

2015-12-02

In this study we analyze and extend mesh-free algorithms for three-dimensional data transfer problems in partitioned multiphysics simulations. We first provide a direct comparison between a mesh-based weighted residual method using the common-refinement scheme and two mesh-free algorithms leveraging compactly supported radial basis functions: one using a spline interpolation and one using a moving least square reconstruction. Through the comparison we assess both the conservation and accuracy of the data transfer obtained from each of the methods. We do so for a varying set of geometries with and without curvature and sharp features and for functions with and without smoothnessmore » and with varying gradients. Our results show that the mesh-based and mesh-free algorithms are complementary with cases where each was demonstrated to perform better than the other. We then focus on the mesh-free methods by developing a set of algorithms to parallelize them based on sparse linear algebra techniques. This includes a discussion of fast parallel radius searching in point clouds and restructuring the interpolation algorithms to leverage data structures and linear algebra services designed for large distributed computing environments. The scalability of our new algorithms is demonstrated on a leadership class computing facility using a set of basic scaling studies. Finally, these scaling studies show that for problems with reasonable load balance, our new algorithms for both spline interpolation and moving least square reconstruction demonstrate both strong and weak scalability using more than 100,000 MPI processes with billions of degrees of freedom in the data transfer operation.« less

Enhancing data locality by using terminal propagation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hendrickson, B.; Leland, R.; Van Driessche, R.

1995-12-31

Terminal propagation is a method developed in the circuit placement community for adding constraints to graph partitioning problems. This paper adapts and expands this idea, and applies it to the problem of partitioning data structures among the processors of a parallel computer. We show how the constraints in terminal propagation can be used to encourage partitions in which messages are communicated only between architecturally near processors. We then show how these constraints can be handled in two important partitioning algorithms, spectral bisection and multilevel-KL. We compare the quality of partitions generated by these algorithms to each other and to Partitionsmore » generated by more familiar techniques.« less

"K"-Balance Partitioning: An Exact Method with Applications to Generalized Structural Balance and Other Psychological Contexts

ERIC Educational Resources Information Center

Brusco, Michael; Steinley, Douglas

2010-01-01

Structural balance theory (SBT) has maintained a venerable status in the psychological literature for more than 5 decades. One important problem pertaining to SBT is the approximation of structural or generalized balance via the partitioning of the vertices of a signed graph into "K" clusters. This "K"-balance partitioning problem also has more…

An optimal repartitioning decision policy

NASA Technical Reports Server (NTRS)

Nicol, D. M.; Reynolds, P. F., Jr.

1986-01-01

A central problem to parallel processing is the determination of an effective partitioning of workload to processors. The effectiveness of any given partition is dependent on the stochastic nature of the workload. The problem of determining when and if the stochastic behavior of the workload has changed enough to warrant the calculation of a new partition is treated. The problem is modeled as a Markov decision process, and an optimal decision policy is derived. Quantification of this policy is usually intractable. A heuristic policy which performs nearly optimally is investigated empirically. The results suggest that the detection of change is the predominant issue in this problem.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

Hardware Index to Set Partition Converter

DTIC Science & Technology

2013-01-01

Brisk, J.G. de Figueiredo Coutinho, P.C. Diniz (Eds.): ARC 2013, LNCS 7806, pp. 72–83, 2013. c© Springer-Verlag Berlin Heidelberg 2013 Report...374 (1990) 13. Orlov, M.: Efficient generation of set partitions (March 2002), http://www.cs.bgu.ac.il/~orlovm/papers/partitions.pdf 14. Reingold, E

Transport in Dynamical Astronomy and Multibody Problems

NASA Astrophysics Data System (ADS)

Dellnitz, Michael; Junge, Oliver; Koon, Wang Sang; Lekien, Francois; Lo, Martin W.; Marsden, Jerrold E.; Padberg, Kathrin; Preis, Robert; Ross, Shane D.; Thiere, Bianca

We combine the techniques of almost invariant sets (using tree structured box elimination and graph partitioning algorithms) with invariant manifold and lobe dynamics techniques. The result is a new computational technique for computing key dynamical features, including almost invariant sets, resonance regions as well as transport rates and bottlenecks between regions in dynamical systems. This methodology can be applied to a variety of multibody problems, including those in molecular modeling, chemical reaction rates and dynamical astronomy. In this paper we focus on problems in dynamical astronomy to illustrate the power of the combination of these different numerical tools and their applicability. In particular, we compute transport rates between two resonance regions for the three-body system consisting of the Sun, Jupiter and a third body (such as an asteroid). These resonance regions are appropriate for certain comets and asteroids.

No-infill 3D Printing

NASA Astrophysics Data System (ADS)

Wei, Xiao-Ran; Zhang, Yu-He; Geng, Guo-Hua

2016-09-01

In this paper, we examined how printing the hollow objects without infill via fused deposition modeling, one of the most widely used 3D-printing technologies, by partitioning the objects to shell parts. More specifically, we linked the partition to the exact cover problem. Given an input watertight mesh shape S, we developed region growing schemes to derive a set of surfaces that had inside surfaces that were printable without support on the mesh for the candidate parts. We then employed Monte Carlo tree search over the candidate parts to obtain the optimal set cover. All possible candidate subsets of exact cover from the optimal set cover were then obtained and the bounded tree was used to search the optimal exact cover. We oriented each shell part to the optimal position to guarantee the inside surface was printed without support, while the outside surface was printed with minimum support. Our solution can be applied to a variety of models, closed-hollowed or semi-closed, with or without holes, as evidenced by experiments and performance evaluation on our proposed algorithm.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range.

PubMed

He, Chenlong; Feng, Zuren; Ren, Zhigang

2018-02-03

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham's Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm.

Distributed Algorithm for Voronoi Partition of Wireless Sensor Networks with a Limited Sensing Range

PubMed Central

Feng, Zuren; Ren, Zhigang

2018-01-01

For Wireless Sensor Networks (WSNs), the Voronoi partition of a region is a challenging problem owing to the limited sensing ability of each sensor and the distributed organization of the network. In this paper, an algorithm is proposed for each sensor having a limited sensing range to compute its limited Voronoi cell autonomously, so that the limited Voronoi partition of the entire WSN is generated in a distributed manner. Inspired by Graham’s Scan (GS) algorithm used to compute the convex hull of a point set, the limited Voronoi cell of each sensor is obtained by sequentially scanning two consecutive bisectors between the sensor and its neighbors. The proposed algorithm called the Boundary Scan (BS) algorithm has a lower computational complexity than the existing Range-Constrained Voronoi Cell (RCVC) algorithm and reaches the lower bound of the computational complexity of the algorithms used to solve the problem of this kind. Moreover, it also improves the time efficiency of a key step in the Adjust-Sensing-Radius (ASR) algorithm used to compute the exact Voronoi cell. Extensive numerical simulations are performed to demonstrate the correctness and effectiveness of the BS algorithm. The distributed realization of the BS combined with a localization algorithm in WSNs is used to justify the WSN nature of the proposed algorithm. PMID:29401649

Response to “Comment on ‘Rethinking first-principles electron transport theories with projection operators: The problems caused by partitioning the basis set’” [J. Chem. Phys. 140, 177103 (2014)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reuter, Matthew G., E-mail: mgreuter@u.northwestern.edu; Harrison, Robert J.

2014-05-07

The thesis of Brandbyge's comment [J. Chem. Phys. 140, 177103 (2014)] is that our operator decoupling condition is immaterial to transport theories, and it appeals to discussions of nonorthogonal basis sets in transport calculations in its arguments. We maintain that the operator condition is to be preferred over the usual matrix conditions and subsequently detail problems in the existing approaches. From this operator perspective, we conclude that nonorthogonal projectors cannot be used and that the projectors must be selected to satisfy the operator decoupling condition. Because these conclusions pertain to operators, the choice of basis set is not germane.

A Comparison of Heuristic Procedures for Minimum within-Cluster Sums of Squares Partitioning

ERIC Educational Resources Information Center

Brusco, Michael J.; Steinley, Douglas

2007-01-01

Perhaps the most common criterion for partitioning a data set is the minimization of the within-cluster sums of squared deviation from cluster centroids. Although optimal solution procedures for within-cluster sums of squares (WCSS) partitioning are computationally feasible for small data sets, heuristic procedures are required for most practical…

Partitioning the Quaternary

NASA Astrophysics Data System (ADS)

Gibbard, Philip L.; Lewin, John

2016-11-01

We review the historical purposes and procedures for stratigraphical division and naming within the Quaternary, and summarize the current requirements for formal partitioning through the International Commission on Stratigraphy (ICS). A raft of new data and evidence has impacted traditional approaches: quasi-continuous records from ocean sediments and ice cores, new numerical dating techniques, and alternative macro-models, such as those provided through Sequence Stratigraphy and Earth-System Science. The practical usefulness of division remains, but there is now greater appreciation of complex Quaternary detail and the modelling of time continua, the latter also extending into the future. There are problems both of commission (what is done, but could be done better) and of omission (what gets left out) in partitioning the Quaternary. These include the challenge set by the use of unconformities as stage boundaries, how to deal with multiphase records in ocean and terrestrial sediments, what happened at the 'Early-Mid- (Middle) Pleistocene Transition', dealing with trends that cross phase boundaries, and the current controversial focus on how to subdivide the Holocene and formally define an 'Anthropocene'.

Efficient algorithms for a class of partitioning problems

NASA Technical Reports Server (NTRS)

Iqbal, M. Ashraf; Bokhari, Shahid H.

1990-01-01

The problem of optimally partitioning the modules of chain- or tree-like tasks over chain-structured or host-satellite multiple computer systems is addressed. This important class of problems includes many signal processing and industrial control applications. Prior research has resulted in a succession of faster exact and approximate algorithms for these problems. Polynomial exact and approximate algorithms are described for this class that are better than any of the previously reported algorithms. The approach is based on a preprocessing step that condenses the given chain or tree structured task into a monotonic chain or tree. The partitioning of this monotonic take can then be carried out using fast search techniques.

Structure of MQ-NMR spin spaces under higher Sn- and ( Sn)↓ G symmetries. II. Γ/ overlineΓ ( S6)↓ O subduced irreps for sixfold spin clusters pertaining to the molecular cage ion, [ 11BH] 62-

NASA Astrophysics Data System (ADS)

Colpa, J. P.; Temme, F. P.

1991-06-01

The structures of higher n-fold spin cluster systems as irreps under the S6/( S6)↓ O groups are derived using combinatorial techniques over permutational fields, namely that of generalized wordlengths (GWL), to generate the invariance and irrep sets over the M ( q) subspaces for the [ A] 6( Ii) clusters, i.e. those derived from sets of identical nuclear spins I i whose magnitude lies between 1/2 ⩽ I i ⩽ 3/2. The partitions and invariance properties of such monoclusters provide the background to an investigation of the structure of bicluster spin problems over both Hilbert and Liouville spaces. Hence, the [λ], [ overlineλ] ( Sn) partitional aspects of the NMR of the borohydride molecular cage-ion, [ 11BH] 62-, arise from the form of GWLs for specific primes ( p) (i.e. in Sn theory sense of an index denoting the number of subfields) and the use of invariance hierarchies under the direct product group of the subduced spin symmetries. Such ( Sn)↓ G spin symmetries have been presented in discussions of the symmetry of many-electron spin systems, e.g. as outlined in the seminal work of Kaplan (1975). Attention is drawn to the role of Sn-inner tensor products and Cayley algebra in explicitly resolving certain problems connected with the non-simple reducibility pertaining to ( M1- M n ( S6) fields once p exceeds 2 (i.e. for clusters of identical higher spins). By partitioning Liouville space derived from the density operator σ(SO (3) × S6) and its analogues under subduced spin symmetries this paper extends both the formalism and practical application of various recent multiquantum techniques to experimental NMR. The present semitheoretical "tool" to factor << kqv | CL(SO (3) × [ overline6]) | k' q' v'>> and matrix representation of the Liouville operator for the subduced direct product symmetry of the total bicluster problem emphasizes Pines' 1988 argument [in Proc. C-th E. Fermi Physics Institute] that sets of selective subproblems exist which are ameniable to analysis of their information content without the need to treat the full problem; he focusses on selective q processes from an experimental viewpoint whereas we emphasize all q, [λ] forms of factoring in the analysis of spin evolution. Finally, we stress the primary theoretical importance of scalar invariants in few- and many-body spin problems in the context of SU2 × Sn dual mappings and associated genealogies.

Variable neighborhood search to solve the vehicle routing problem for hazardous materials transportation.

PubMed

Bula, Gustavo Alfredo; Prodhon, Caroline; Gonzalez, Fabio Augusto; Afsar, H Murat; Velasco, Nubia

2017-02-15

This work focuses on the Heterogeneous Fleet Vehicle Routing problem (HFVRP) in the context of hazardous materials (HazMat) transportation. The objective is to determine a set of routes that minimizes the total expected routing risk. This is a nonlinear function, and it depends on the vehicle load and the population exposed when an incident occurs. Thus, a piecewise linear approximation is used to estimate it. For solving the problem, a variant of the Variable Neighborhood Search (VNS) algorithm is employed. To improve its performance, a post-optimization procedure is implemented via a Set Partitioning (SP) problem. The SP is solved on a pool of routes obtained from executions of the local search procedure embedded on the VNS. The algorithm is tested on two sets of HFVRP instances based on literature with up to 100 nodes, these instances are modified to include vehicle and arc risk parameters. The results are competitive in terms of computational efficiency and quality attested by a comparison with Mixed Integer Linear Programming (MILP) previously proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Gumaste, U.; Ronaghi, M.

1994-01-01

Applications are described of high-performance parallel, computation for the analysis of complete jet engines, considering its multi-discipline coupled problem. The coupled problem involves interaction of structures with gas dynamics, heat conduction and heat transfer in aircraft engines. The methodology issues addressed include: consistent discrete formulation of coupled problems with emphasis on coupling phenomena; effect of partitioning strategies, augmentation and temporal solution procedures; sensitivity of response to problem parameters; and methods for interfacing multiscale discretizations in different single fields. The computer implementation issues addressed include: parallel treatment of coupled systems; domain decomposition and mesh partitioning strategies; data representation in object-oriented form and mapping to hardware driven representation, and tradeoff studies between partitioning schemes and fully coupled treatment.

Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir Hossein; Goldbert, Alan; Bagasol, Leonard Neil; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir H.; Goldberg, Alan T.; Bagasol, Leonard N.; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Visualizing phylogenetic tree landscapes.

PubMed

Wilgenbusch, James C; Huang, Wen; Gallivan, Kyle A

2017-02-02

Genomic-scale sequence alignments are increasingly used to infer phylogenies in order to better understand the processes and patterns of evolution. Different partitions within these new alignments (e.g., genes, codon positions, and structural features) often favor hundreds if not thousands of competing phylogenies. Summarizing and comparing phylogenies obtained from multi-source data sets using current consensus tree methods discards valuable information and can disguise potential methodological problems. Discovery of efficient and accurate dimensionality reduction methods used to display at once in 2- or 3- dimensions the relationship among these competing phylogenies will help practitioners diagnose the limits of current evolutionary models and potential problems with phylogenetic reconstruction methods when analyzing large multi-source data sets. We introduce several dimensionality reduction methods to visualize in 2- and 3-dimensions the relationship among competing phylogenies obtained from gene partitions found in three mid- to large-size mitochondrial genome alignments. We test the performance of these dimensionality reduction methods by applying several goodness-of-fit measures. The intrinsic dimensionality of each data set is also estimated to determine whether projections in 2- and 3-dimensions can be expected to reveal meaningful relationships among trees from different data partitions. Several new approaches to aid in the comparison of different phylogenetic landscapes are presented. Curvilinear Components Analysis (CCA) and a stochastic gradient decent (SGD) optimization method give the best representation of the original tree-to-tree distance matrix for each of the three- mitochondrial genome alignments and greatly outperformed the method currently used to visualize tree landscapes. The CCA + SGD method converged at least as fast as previously applied methods for visualizing tree landscapes. We demonstrate for all three mtDNA alignments that 3D projections significantly increase the fit between the tree-to-tree distances and can facilitate the interpretation of the relationship among phylogenetic trees. We demonstrate that the choice of dimensionality reduction method can significantly influence the spatial relationship among a large set of competing phylogenetic trees. We highlight the importance of selecting a dimensionality reduction method to visualize large multi-locus phylogenetic landscapes and demonstrate that 3D projections of mitochondrial tree landscapes better capture the relationship among the trees being compared.

An integer programming formulation of the parsimonious loss of heterozygosity problem.

PubMed

Catanzaro, Daniele; Labbé, Martine; Halldórsson, Bjarni V

2013-01-01

A loss of heterozygosity (LOH) event occurs when, by the laws of Mendelian inheritance, an individual should be heterozygote at a given site but, due to a deletion polymorphism, is not. Deletions play an important role in human disease and their detection could provide fundamental insights for the development of new diagnostics and treatments. In this paper, we investigate the parsimonious loss of heterozygosity problem (PLOHP), i.e., the problem of partitioning suspected polymorphisms from a set of individuals into a minimum number of deletion areas. Specifically, we generalize Halldórsson et al.'s work by providing a more general formulation of the PLOHP and by showing how one can incorporate different recombination rates and prior knowledge about the locations of deletions. Moreover, we show that the PLOHP can be formulated as a specific version of the clique partition problem in a particular class of graphs called undirected catch-point interval graphs and we prove its general $({\\cal NP})$-hardness. Finally, we provide a state-of-the-art integer programming (IP) formulation and strengthening valid inequalities to exactly solve real instances of the PLOHP containing up to 9,000 individuals and 3,000 SNPs. Our results give perspectives on the mathematics of the PLOHP and suggest new directions on the development of future efficient exact solution approaches.

Managing Network Partitions in Structured P2P Networks

NASA Astrophysics Data System (ADS)

Shafaat, Tallat M.; Ghodsi, Ali; Haridi, Seif

Structured overlay networks form a major class of peer-to-peer systems, which are touted for their abilities to scale, tolerate failures, and self-manage. Any long-lived Internet-scale distributed system is destined to face network partitions. Consequently, the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems. This makes it a crucial requirement for building any structured peer-to-peer systems to be resilient to network partitions. Although the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems, it has hardly been studied in the context of structured peer-to-peer systems. Structured overlays have mainly been studied under churn (frequent joins/failures), which as a side effect solves the problem of network partitions, as it is similar to massive node failures. Yet, the crucial aspect of network mergers has been ignored. In fact, it has been claimed that ring-based structured overlay networks, which constitute the majority of the structured overlays, are intrinsically ill-suited for merging rings. In this chapter, we motivate the problem of network partitions and mergers in structured overlays. We discuss how a structured overlay can automatically detect a network partition and merger. We present an algorithm for merging multiple similar ring-based overlays when the underlying network merges. We examine the solution in dynamic conditions, showing how our solution is resilient to churn during the merger, something widely believed to be difficult or impossible. We evaluate the algorithm for various scenarios and show that even when falsely detecting a merger, the algorithm quickly terminates and does not clutter the network with many messages. The algorithm is flexible as the tradeoff between message complexity and time complexity can be adjusted by a parameter.

Scheduling Independent Partitions in Integrated Modular Avionics Systems

PubMed Central

Du, Chenglie; Han, Pengcheng

2016-01-01

Recently the integrated modular avionics (IMA) architecture has been widely adopted by the avionics industry due to its strong partition mechanism. Although the IMA architecture can achieve effective cost reduction and reliability enhancement in the development of avionics systems, it results in a complex allocation and scheduling problem. All partitions in an IMA system should be integrated together according to a proper schedule such that their deadlines will be met even under the worst case situations. In order to help provide a proper scheduling table for all partitions in IMA systems, we study the schedulability of independent partitions on a multiprocessor platform in this paper. We firstly present an exact formulation to calculate the maximum scaling factor and determine whether all partitions are schedulable on a limited number of processors. Then with a Game Theory analogy, we design an approximation algorithm to solve the scheduling problem of partitions, by allowing each partition to optimize its own schedule according to the allocations of the others. Finally, simulation experiments are conducted to show the efficiency and reliability of the approach proposed in terms of time consumption and acceptance ratio. PMID:27942013

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian

1992-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip H.; Garg, Sanjay; Holowecky, Brian R.

1993-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

Allan Variance Calculation for Nonuniformly Spaced Input Data

DTIC Science & Technology

2015-01-01

τ (tau). First, the set of gyro values is partitioned into bins of duration τ. For example, if the sampling duration τ is 2 sec and there are 4,000...Variance Calculation For each value of τ, the conventional AV calculation partitions the gyro data sets into bins with approximately τ / Δt...value of Δt. Therefore, a new way must be found to partition the gyro data sets into bins. The basic concept behind the modified AV calculation is

An Efficient Algorithm for Partitioning and Authenticating Problem-Solutions of eLeaming Contents

ERIC Educational Resources Information Center

Dewan, Jahangir; Chowdhury, Morshed; Batten, Lynn

2013-01-01

Content authenticity and correctness is one of the important challenges in eLearning as there can be many solutions to one specific problem in cyber space. Therefore, the authors feel it is necessary to map problems to solutions using graph partition and weighted bipartite matching. This article proposes an efficient algorithm to partition…

Optimal steering for kinematic vehicles with applications to spatially distributed agents

NASA Astrophysics Data System (ADS)

Brown, Scott; Praeger, Cheryl E.; Giudici, Michael

While there is no universal method to address control problems involving networks of autonomous vehicles, there exist a few promising schemes that apply to different specific classes of problems, which have attracted the attention of many researchers from different fields. In particular, one way to extend techniques that address problems involving a single autonomous vehicle to those involving teams of autonomous vehicles is to use the concept of Voronoi diagram. The Voronoi diagram provides a spatial partition of the environment the team of vehicles operate in, where each element of this partition is associated with a unique vehicle from the team. The partition induces a graph abstraction of the operating space that is in an one-to-one correspondence with the network abstraction of the team of autonomous vehicles; a fact that can provide both conceptual and analytical advantages during mission planning and execution. In this dissertation, we propose the use of a new class of Voronoi-like partitioning schemes with respect to state-dependent proximity (pseudo-) metrics rather than the Euclidean distance or other generalized distance functions, which are typically used in the literature. An important nuance here is that, in contrast to the Euclidean distance, state-dependent metrics can succinctly capture system theoretic features of each vehicle from the team (e.g., vehicle kinematics), as well as the environment-vehicle interactions, which are induced, for example, by local winds/currents. We subsequently illustrate how the proposed concept of state-dependent Voronoi-like partition can induce local control schemes for problems involving networks of spatially distributed autonomous vehicles by examining a sequential pursuit problem of a maneuvering target by a group of pursuers distributed in the plane. The construction of generalized Voronoi diagrams with respect to state-dependent metrics poses some significant challenges. First, the generalized distance metric may be a function of the direction of motion of the vehicle (anisotropic pseudo-distance function) and/or may not be expressible in closed form. Second, such problems fall under the general class of partitioning problems for which the vehicles' dynamics must be taken into account. The topology of the vehicle's configuration space may be non-Euclidean, for example, it may be a manifold embedded in a Euclidean space. In other words, these problems may not be reducible to generalized Voronoi diagram problems for which efficient construction schemes, analytical and/or computational, exist in the literature. This research effort pursues three main objectives. First, we present the complete solution of different steering problems involving a single vehicle in the presence of motion constraints imposed by the maneuverability envelope of the vehicle and/or the presence of a drift field induced by winds/currents in its vicinity. The analysis of each steering problem involving a single vehicle provides us with a state-dependent generalized metric, such as the minimum time-to-go/come. We subsequently use these state-dependent generalized distance functions as the proximity metrics in the formulation of generalized Voronoi-like partitioning problems. The characterization of the solutions of these state-dependent Voronoi-like partitioning problems using either analytical or computational techniques constitutes the second main objective of this dissertation. The third objective of this research effort is to illustrate the use of the proposed concept of state-dependent Voronoi-like partition as a means for passing from control techniques that apply to problems involving a single vehicle to problems involving networks of spatially distributed autonomous vehicles. To this aim, we formulate the problem of sequential/relay pursuit of a maneuvering target by a group of spatially distributed pursuers and subsequently propose a distributed group pursuit strategy that directly derives from the solution of a state-dependent Voronoi-like partitioning problem. (Abstract shortened by UMI.)

How to cluster in parallel with neural networks

NASA Technical Reports Server (NTRS)

Kamgar-Parsi, Behzad; Gualtieri, J. A.; Devaney, Judy E.; Kamgar-Parsi, Behrooz

1988-01-01

Partitioning a set of N patterns in a d-dimensional metric space into K clusters - in a way that those in a given cluster are more similar to each other than the rest - is a problem of interest in astrophysics, image analysis and other fields. As there are approximately K(N)/K (factorial) possible ways of partitioning the patterns among K clusters, finding the best solution is beyond exhaustive search when N is large. Researchers show that this problem can be formulated as an optimization problem for which very good, but not necessarily optimal solutions can be found by using a neural network. To do this the network must start from many randomly selected initial states. The network is simulated on the MPP (a 128 x 128 SIMD array machine), where researchers use the massive parallelism not only in solving the differential equations that govern the evolution of the network, but also by starting the network from many initial states at once, thus obtaining many solutions in one run. Researchers obtain speedups of two to three orders of magnitude over serial implementations and the promise through Analog VLSI implementations of speedups comensurate with human perceptual abilities.

Site partitioning for distributed redundant disk arrays

NASA Technical Reports Server (NTRS)

Mourad, Antoine N.; Fuchs, W. K.; Saab, Daniel G.

1992-01-01

Distributed redundant disk arrays can be used in a distributed computing system or database system to provide recovery in the presence of temporary and permanent failures of single sites. In this paper, we look at the problem of partitioning the sites into redundant arrays in such way that the communication costs for maintaining the parity information are minimized. We show that the partitioning problem is NP-complete and we propose two heuristic algorithms for finding approximate solutions.

Multiply scaled constrained nonlinear equation solvers. [for nonlinear heat conduction problems

NASA Technical Reports Server (NTRS)

Padovan, Joe; Krishna, Lala

1986-01-01

To improve the numerical stability of nonlinear equation solvers, a partitioned multiply scaled constraint scheme is developed. This scheme enables hierarchical levels of control for nonlinear equation solvers. To complement the procedure, partitioned convergence checks are established along with self-adaptive partitioning schemes. Overall, such procedures greatly enhance the numerical stability of the original solvers. To demonstrate and motivate the development of the scheme, the problem of nonlinear heat conduction is considered. In this context the main emphasis is given to successive substitution-type schemes. To verify the improved numerical characteristics associated with partitioned multiply scaled solvers, results are presented for several benchmark examples.

Partition functions of thermally dissociating diatomic molecules and related momentum problem

NASA Astrophysics Data System (ADS)

Buchowiecki, Marcin

2017-11-01

The anharmonicity and ro-vibrational coupling in ro-vibrational partition functions of diatomic molecules are analyzed for the high temperatures of the thermal dissociation regime. The numerically exact partition functions and thermal energies are calculated. At the high temperatures the proper integration of momenta is important if the partition function of the molecule, understood as bounded system, is to be obtained. The problem of proper treatment of momentum is crucial for correctness of high temperature molecular simulations as the decomposition of simulated molecule have to be avoided; the analysis of O2, H2+, and NH3 molecules allows to show importance of βDe value.

Site Partitioning for Redundant Arrays of Distributed Disks

NASA Technical Reports Server (NTRS)

Mourad, Antoine N.; Fuchs, W. Kent; Saab, Daniel G.

1996-01-01

Redundant arrays of distributed disks (RADD) can be used in a distributed computing system or database system to provide recovery in the presence of disk crashes and temporary and permanent failures of single sites. In this paper, we look at the problem of partitioning the sites of a distributed storage system into redundant arrays in such a way that the communication costs for maintaining the parity information are minimized. We show that the partitioning problem is NP-hard. We then propose and evaluate several heuristic algorithms for finding approximate solutions. Simulation results show that significant reduction in remote parity update costs can be achieved by optimizing the site partitioning scheme.

A modified approach to controller partitioning

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Veillette, Robert J.

1993-01-01

The idea of computing a decentralized control law for the integrated flight/propulsion control of an aircraft by partitioning a given centralized controller is investigated. An existing controller partitioning methodology is described, and a modified approach is proposed with the objective of simplifying the associated controller approximation problem. Under the existing approach, the decentralized control structure is a variable in the partitioning process; by contrast, the modified approach assumes that the structure is fixed a priori. Hence, the centralized controller design may take the decentralized control structure into account. Specifically, the centralized controller may be designed to include all the same inputs and outputs as the decentralized controller; then, the two controllers may be compared directly, simplifying the partitioning process considerably. Following the modified approach, a centralized controller is designed for an example aircraft mode. The design includes all the inputs and outputs to be used in a specified decentralized control structure. However, it is shown that the resulting centralized controller is not well suited for approximation by a decentralized controller of the given structure. The results indicate that it is not practical in general to cast the controller partitioning problem as a direct controller approximation problem.

Cluster Stability Estimation Based on a Minimal Spanning Trees Approach

NASA Astrophysics Data System (ADS)

Volkovich, Zeev (Vladimir); Barzily, Zeev; Weber, Gerhard-Wilhelm; Toledano-Kitai, Dvora

2009-08-01

Among the areas of data and text mining which are employed today in science, economy and technology, clustering theory serves as a preprocessing step in the data analyzing. However, there are many open questions still waiting for a theoretical and practical treatment, e.g., the problem of determining the true number of clusters has not been satisfactorily solved. In the current paper, this problem is addressed by the cluster stability approach. For several possible numbers of clusters we estimate the stability of partitions obtained from clustering of samples. Partitions are considered consistent if their clusters are stable. Clusters validity is measured as the total number of edges, in the clusters' minimal spanning trees, connecting points from different samples. Actually, we use the Friedman and Rafsky two sample test statistic. The homogeneity hypothesis, of well mingled samples within the clusters, leads to asymptotic normal distribution of the considered statistic. Resting upon this fact, the standard score of the mentioned edges quantity is set, and the partition quality is represented by the worst cluster corresponding to the minimal standard score value. It is natural to expect that the true number of clusters can be characterized by the empirical distribution having the shortest left tail. The proposed methodology sequentially creates the described value distribution and estimates its left-asymmetry. Numerical experiments, presented in the paper, demonstrate the ability of the approach to detect the true number of clusters.

Can Moral Hazard Be Resolved by Common-Knowledge in S4n-Knowledge?

NASA Astrophysics Data System (ADS)

Matsuhisa, Takashi

This article investigates the relationship between common-knowledge and agreement in multi-agent system, and to apply the agreement result by common-knowledge to the principal-agent model under non-partition information. We treat the two problems: (1) how we capture the fact that the agents agree on an event or they get consensus on it from epistemic point of view, and (2) how the agreement theorem will be able to make progress to settle a moral hazard problem in the principal-agents model under non-partition information. We shall propose a solution program for the moral hazard in the principal-agents model under non-partition information by common-knowledge. Let us start that the agents have the knowledge structure induced from a reflexive and transitive relation associated with the multi-modal logic S4n. Each agent obtains the membership value of an event under his/her private information, so he/she considers the event as fuzzy set. Specifically consider the situation that the agents commonly know all membership values of the other agents. In this circumstance we shall show the agreement theorem that consensus on the membership values among all agents can still be guaranteed. Furthermore, under certain assumptions we shall show that the moral hazard can be resolved in the principal-agent model when all the expected marginal costs are common-knowledge among the principal and agents.

Certificate Revocation Using Fine Grained Certificate Space Partitioning

NASA Astrophysics Data System (ADS)

Goyal, Vipul

A new certificate revocation system is presented. The basic idea is to divide the certificate space into several partitions, the number of partitions being dependent on the PKI environment. Each partition contains the status of a set of certificates. A partition may either expire or be renewed at the end of a time slot. This is done efficiently using hash chains.

Analysis of Partitioned Methods for the Biot System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bukac, Martina; Layton, William; Moraiti, Marina

2015-02-18

In this work, we present a comprehensive study of several partitioned methods for the coupling of flow and mechanics. We derive energy estimates for each method for the fully-discrete problem. We write the obtained stability conditions in terms of a key control parameter defined as a ratio of the coupling strength and the speed of propagation. Depending on the parameters in the problem, give the choice of the partitioned method which allows the largest time step. (C) 2015 Wiley Periodicals, Inc.

A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning.

PubMed

Zhang, H H; Gao, S; Chen, W; Shi, L; D'Souza, W D; Meyer, R R

2013-03-21

An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equallyspaced beams (eplans), we have developed a global search metaheuristic process based on the nested partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are of superior quality.

A surrogate-based metaheuristic global search method for beam angle selection in radiation treatment planning

PubMed Central

Zhang, H H; Gao, S; Chen, W; Shi, L; D’Souza, W D; Meyer, R R

2013-01-01

An important element of radiation treatment planning for cancer therapy is the selection of beam angles (out of all possible coplanar and non-coplanar angles in relation to the patient) in order to maximize the delivery of radiation to the tumor site and minimize radiation damage to nearby organs-at-risk. This category of combinatorial optimization problem is particularly difficult because direct evaluation of the quality of treatment corresponding to any proposed selection of beams requires the solution of a large-scale dose optimization problem involving many thousands of variables that represent doses delivered to volume elements (voxels) in the patient. However, if the quality of angle sets can be accurately estimated without expensive computation, a large number of angle sets can be considered, increasing the likelihood of identifying a very high quality set. Using a computationally efficient surrogate beam set evaluation procedure based on single-beam data extracted from plans employing equally-spaced beams (eplans), we have developed a global search metaheuristic process based on the Nested Partitions framework for this combinatorial optimization problem. The surrogate scoring mechanism allows us to assess thousands of beam set samples within a clinically acceptable time frame. Tests on difficult clinical cases demonstrate that the beam sets obtained via our method are superior quality. PMID:23459411

PuLP/XtraPuLP : Partitioning Tools for Extreme-Scale Graphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slota, George M; Rajamanickam, Sivasankaran; Madduri, Kamesh

2017-09-21

PuLP/XtraPulp is software for partitioning graphs from several real-world problems. Graphs occur in several places in real world from road networks, social networks and scientific simulations. For efficient parallel processing these graphs have to be partitioned (split) with respect to metrics such as computation and communication costs. Our software allows such partitioning for massive graphs.

A strategy to load balancing for non-connectivity MapReduce job

NASA Astrophysics Data System (ADS)

Zhou, Huaping; Liu, Guangzong; Gui, Haixia

2017-09-01

MapReduce has been widely used in large scale and complex datasets as a kind of distributed programming model. Original Hash partitioning function in MapReduce often results the problem of data skew when data distribution is uneven. To solve the imbalance of data partitioning, we proposes a strategy to change the remaining partitioning index when data is skewed. In Map phase, we count the amount of data which will be distributed to each reducer, then Job Tracker monitor the global partitioning information and dynamically modify the original partitioning function according to the data skew model, so the Partitioner can change the index of these partitioning which will cause data skew to the other reducer that has less load in the next partitioning process, and can eventually balance the load of each node. Finally, we experimentally compare our method with existing methods on both synthetic and real datasets, the experimental results show our strategy can solve the problem of data skew with better stability and efficiency than Hash method and Sampling method for non-connectivity MapReduce task.

The partition dimension of cycle books graph

NASA Astrophysics Data System (ADS)

Santoso, Jaya; Darmaji

2018-03-01

Let G be a nontrivial and connected graph with vertex set V(G), edge set E(G) and S ⊆ V(G) with v ∈ V(G), the distance between v and S is d(v,S) = min{d(v,x)|x ∈ S}. For an ordered partition ∏ = {S 1, S 2, S 3,…, Sk } of V(G), the representation of v with respect to ∏ is defined by r(v|∏) = (d(v, S 1), d(v, S 2),…, d(v, Sk )). The partition ∏ is called a resolving partition of G if all representations of vertices are distinct. The partition dimension pd(G) is the smallest integer k such that G has a resolving partition set with k members. In this research, we will determine the partition dimension of Cycle Books {B}{Cr,m}. Cycle books graph {B}{Cr,m} is a graph consisting of m copies cycle Cr with the common path P 2. It is shown that the partition dimension of cycle books graph, pd({B}{C3,m}) is 3 for m = 2, 3, and m for m ≥ 4. pd({B}{C4,m}) is 3 + 2k for m = 3k + 2, 4 + 2(k ‑ 1) for m = 3k + 1, and 3 + 2(k ‑ 1) for m = 3k. pd({B}{C5,m}) is m + 1.

Surface smoothing and template partitioning for cranial implant CAD

NASA Astrophysics Data System (ADS)

Min, Kyoung-june; Dean, David

2005-04-01

Employing patient-specific prefabricated implants can be an effective treatment for large cranial defects (i.e., > 25 cm2). We have previously demonstrated the use of Computer Aided Design (CAD) software that starts with the patient"s 3D head CT-scan. A template is accurately matched to the pre-detected skull defect margin. For unilateral cranial defects the template is derived from a left-to-right mirrored skull image. However, two problems arise: (1) slice edge artifacts generated during isosurface polygonalization are inherited by the final implant; and (2) partitioning (i.e., cookie-cutting) the implant surface from the mirrored skull image usually results in curvature discontinuities across the interface between the patient"s defect and the implant. To solve these problems, we introduce a novel space curve-to-surface partitioning algorithm following a ray-casting surface re-sampling and smoothing procedure. Specifically, the ray-cast re-sampling is followed by bilinear interpolation and low-pass filtering. The resulting surface has a highly regular grid-like topological structure of quadrilaterally arranged triangles. Then, we replace the regions to be partitioned with predefined sets of triangular elements thereby cutting the template surface to accurately fit the defect margin at high resolution and without surface curvature discontinuities. Comparisons of the CAD implants for five patients against the manually generated implant that the patient actually received show an average implant-patient gap of 0.45mm for the former and 2.96mm for the latter. Also, average maximum normalized curvature of interfacing surfaces was found to be smoother, 0.043, for the former than the latter, 0.097. This indicates that the CAD implants would provide a significantly better fit.

Multiple-solution problems in a statistics classroom: an example

NASA Astrophysics Data System (ADS)

Chu, Chi Wing; Chan, Kevin L. T.; Chan, Wai-Sum; Kwong, Koon-Shing

2017-11-01

The mathematics education literature shows that encouraging students to develop multiple solutions for given problems has a positive effect on students' understanding and creativity. In this paper, we present an example of multiple-solution problems in statistics involving a set of non-traditional dice. In particular, we consider the exact probability mass distribution for the sum of face values. Four different ways of solving the problem are discussed. The solutions span various basic concepts in different mathematical disciplines (sample space in probability theory, the probability generating function in statistics, integer partition in basic combinatorics and individual risk model in actuarial science) and thus promotes upper undergraduate students' awareness of knowledge connections between their courses. All solutions of the example are implemented using the R statistical software package.

Polynomial-Time Approximation Algorithm for the Problem of Cardinality-Weighted Variance-Based 2-Clustering with a Given Center

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Motkova, A. V.

2018-01-01

A strongly NP-hard problem of partitioning a finite set of points of Euclidean space into two clusters is considered. The solution criterion is the minimum of the sum (over both clusters) of weighted sums of squared distances from the elements of each cluster to its geometric center. The weights of the sums are equal to the cardinalities of the desired clusters. The center of one cluster is given as input, while the center of the other is unknown and is determined as the point of space equal to the mean of the cluster elements. A version of the problem is analyzed in which the cardinalities of the clusters are given as input. A polynomial-time 2-approximation algorithm for solving the problem is constructed.

Parameterizing by the Number of Numbers

NASA Astrophysics Data System (ADS)

Fellows, Michael R.; Gaspers, Serge; Rosamond, Frances A.

The usefulness of parameterized algorithmics has often depended on what Niedermeier has called "the art of problem parameterization". In this paper we introduce and explore a novel but general form of parameterization: the number of numbers. Several classic numerical problems, such as Subset Sum, Partition, 3-Partition, Numerical 3-Dimensional Matching, and Numerical Matching with Target Sums, have multisets of integers as input. We initiate the study of parameterizing these problems by the number of distinct integers in the input. We rely on an FPT result for Integer Linear Programming Feasibility to show that all the above-mentioned problems are fixed-parameter tractable when parameterized in this way. In various applied settings, problem inputs often consist in part of multisets of integers or multisets of weighted objects (such as edges in a graph, or jobs to be scheduled). Such number-of-numbers parameterized problems often reduce to subproblems about transition systems of various kinds, parameterized by the size of the system description. We consider several core problems of this kind relevant to number-of-numbers parameterization. Our main hardness result considers the problem: given a non-deterministic Mealy machine M (a finite state automaton outputting a letter on each transition), an input word x, and a census requirement c for the output word specifying how many times each letter of the output alphabet should be written, decide whether there exists a computation of M reading x that outputs a word y that meets the requirement c. We show that this problem is hard for W[1]. If the question is whether there exists an input word x such that a computation of M on x outputs a word that meets c, the problem becomes fixed-parameter tractable.

Optimal parallel solution of sparse triangular systems

NASA Technical Reports Server (NTRS)

Alvarado, Fernando L.; Schreiber, Robert

1990-01-01

A method for the parallel solution of triangular sets of equations is described that is appropriate when there are many right-handed sides. By preprocessing, the method can reduce the number of parallel steps required to solve Lx = b compared to parallel forward or backsolve. Applications are to iterative solvers with triangular preconditioners, to structural analysis, or to power systems applications, where there may be many right-handed sides (not all available a priori). The inverse of L is represented as a product of sparse triangular factors. The problem is to find a factored representation of this inverse of L with the smallest number of factors (or partitions), subject to the requirement that no new nonzero elements be created in the formation of these inverse factors. A method from an earlier reference is shown to solve this problem. This method is improved upon by constructing a permutation of the rows and columns of L that preserves triangularity and allow for the best possible such partition. A number of practical examples and algorithmic details are presented. The parallelism attainable is illustrated by means of elimination trees and clique trees.

A Dimensionally Reduced Clustering Methodology for Heterogeneous Occupational Medicine Data Mining.

PubMed

Saâdaoui, Foued; Bertrand, Pierre R; Boudet, Gil; Rouffiac, Karine; Dutheil, Frédéric; Chamoux, Alain

2015-10-01

Clustering is a set of techniques of the statistical learning aimed at finding structures of heterogeneous partitions grouping homogenous data called clusters. There are several fields in which clustering was successfully applied, such as medicine, biology, finance, economics, etc. In this paper, we introduce the notion of clustering in multifactorial data analysis problems. A case study is conducted for an occupational medicine problem with the purpose of analyzing patterns in a population of 813 individuals. To reduce the data set dimensionality, we base our approach on the Principal Component Analysis (PCA), which is the statistical tool most commonly used in factorial analysis. However, the problems in nature, especially in medicine, are often based on heterogeneous-type qualitative-quantitative measurements, whereas PCA only processes quantitative ones. Besides, qualitative data are originally unobservable quantitative responses that are usually binary-coded. Hence, we propose a new set of strategies allowing to simultaneously handle quantitative and qualitative data. The principle of this approach is to perform a projection of the qualitative variables on the subspaces spanned by quantitative ones. Subsequently, an optimal model is allocated to the resulting PCA-regressed subspaces.

Direct optimization, affine gap costs, and node stability.

PubMed

Aagesen, Lone

2005-09-01

The outcome of a phylogenetic analysis based on DNA sequence data is highly dependent on the homology-assignment step and may vary with alignment parameter costs. Robustness to changes in parameter costs is therefore a desired quality of a data set because the final conclusions will be less dependent on selecting a precise optimal cost set. Here, node stability is explored in relationship to separate versus combined analysis in three different data sets, all including several data partitions. Robustness to changes in cost sets is measured as number of successive changes that can be made in a given cost set before a specific clade is lost. The changes are in all cases base change cost, gap penalties, and adding/removing/changing affine gap costs. When combining data partitions, the number of clades that appear in the entire parameter space is not remarkably increased, in some cases this number even decreased. However, when combining data partitions the trees from cost sets including affine gap costs were always more similar than the trees were from cost sets without affine gap costs. This was not the case when the data partitions were analyzed independently. When data sets were combined approximately 80% of the clades found under cost sets including affine gap costs resisted at least one change to the cost set.

Cartesian control of redundant robots

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.

1989-01-01

A Cartesian-space position/force controller is presented for redundant robots. The proposed control structure partitions the control problem into a nonredundant position/force trajectory tracking problem and a redundant mapping problem between Cartesian control input F is a set member of the set R(sup m) and robot actuator torque T is a set member of the set R(sup n) (for redundant robots, m is less than n). The underdetermined nature of the F yields T map is exploited so that the robot redundancy is utilized to improve the dynamic response of the robot. This dynamically optimal F yields T map is implemented locally (in time) so that it is computationally efficient for on-line control; however, it is shown that the map possesses globally optimal characteristics. Additionally, it is demonstrated that the dynamically optimal F yields T map can be modified so that the robot redundancy is used to simultaneously improve the dynamic response and realize any specified kinematic performance objective (e.g., manipulability maximization or obstacle avoidance). Computer simulation results are given for a four degree of freedom planar redundant robot under Cartesian control, and demonstrate that position/force trajectory tracking and effective redundancy utilization can be achieved simultaneously with the proposed controller.

QSPR modeling of octanol/water partition coefficient for vitamins by optimal descriptors calculated with SMILES.

PubMed

Toropov, A A; Toropova, A P; Raska, I

2008-04-01

Simplified molecular input line entry system (SMILES) has been utilized in constructing quantitative structure-property relationships (QSPR) for octanol/water partition coefficient of vitamins and organic compounds of different classes by optimal descriptors. Statistical characteristics of the best model (vitamins) are the following: n=17, R(2)=0.9841, s=0.634, F=931 (training set); n=7, R(2)=0.9928, s=0.773, F=690 (test set). Using this approach for modeling octanol/water partition coefficient for a set of organic compounds gives a model that is statistically characterized by n=69, R(2)=0.9872, s=0.156, F=5184 (training set) and n=70, R(2)=0.9841, s=0.179, F=4195 (test set).

Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Crowley, Kay; Saltz, Joel; Mirchandaney, Ravi; Berryman, Harry

1989-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Run-time scheduling and execution of loops on message passing machines

NASA Technical Reports Server (NTRS)

Saltz, Joel; Crowley, Kathleen; Mirchandaney, Ravi; Berryman, Harry

1990-01-01

Sparse system solvers and general purpose codes for solving partial differential equations are examples of the many types of problems whose irregularity can result in poor performance on distributed memory machines. Often, the data structures used in these problems are very flexible. Crucial details concerning loop dependences are encoded in these structures rather than being explicitly represented in the program. Good methods for parallelizing and partitioning these types of problems require assignment of computations in rather arbitrary ways. Naive implementations of programs on distributed memory machines requiring general loop partitions can be extremely inefficient. Instead, the scheduling mechanism needs to capture the data reference patterns of the loops in order to partition the problem. First, the indices assigned to each processor must be locally numbered. Next, it is necessary to precompute what information is needed by each processor at various points in the computation. The precomputed information is then used to generate an execution template designed to carry out the computation, communication, and partitioning of data, in an optimized manner. The design is presented for a general preprocessor and schedule executer, the structures of which do not vary, even though the details of the computation and of the type of information are problem dependent.

Haplotyping for disease association: a combinatorial approach.

PubMed

Lancia, Giuseppe; Ravi, R; Rizzi, Romeo

2008-01-01

We consider a combinatorial problem derived from haplotyping a population with respect to a genetic disease, either recessive or dominant. Given a set of individuals, partitioned into healthy and diseased, and the corresponding sets of genotypes, we want to infer "bad'' and "good'' haplotypes to account for these genotypes and for the disease. Assume e.g. the disease is recessive. Then, the resolving haplotypes must consist of bad and good haplotypes, so that (i) each genotype belonging to a diseased individual is explained by a pair of bad haplotypes and (ii) each genotype belonging to a healthy individual is explained by a pair of haplotypes of which at least one is good. We prove that the associated decision problem is NP-complete. However, we also prove that there is a simple solution, provided the data satisfy a very weak requirement.

Study of energy partitioning using a set of related explosive formulations

NASA Astrophysics Data System (ADS)

Lieber, Mark; Foster, Joseph C.; Stewart, D. Scott

2012-03-01

Condensed phase high explosives convert potential energy stored in the electro-magnetic field structure of complex molecules to high power output during the detonation process. Historically, the explosive design problem has focused on intramolecular energy storage. The molecules of interest are derived via molecular synthesis providing near stoichiometric balance on the physical scale of the molecule. This approach provides prompt reactions based on transport physics at the molecular scale. Modern material design has evolved to approaches that employ intermolecular ingredients to alter the spatial and temporal distribution of energy release. State of the art continuum methods have been used to study this approach to the materials design. Cheetah has been used to produce data for a set of fictitious explosive formulations based on C-4 to study the partitioning of the available energy between internal and kinetic energy in the detonation. The equation of state information from Cheetah has been used in ALE3D to develop an understanding of the relationship between variations in the formulation parameters and the internal energy cycle in the products.

Comparative study of feature selection with ensemble learning using SOM variants

NASA Astrophysics Data System (ADS)

Filali, Ameni; Jlassi, Chiraz; Arous, Najet

2017-03-01

Ensemble learning has succeeded in the growth of stability and clustering accuracy, but their runtime prohibits them from scaling up to real-world applications. This study deals the problem of selecting a subset of the most pertinent features for every cluster from a dataset. The proposed method is another extension of the Random Forests approach using self-organizing maps (SOM) variants to unlabeled data that estimates the out-of-bag feature importance from a set of partitions. Every partition is created using a various bootstrap sample and a random subset of the features. Then, we show that the process internal estimates are used to measure variable pertinence in Random Forests are also applicable to feature selection in unsupervised learning. This approach aims to the dimensionality reduction, visualization and cluster characterization at the same time. Hence, we provide empirical results on nineteen benchmark data sets indicating that RFS can lead to significant improvement in terms of clustering accuracy, over several state-of-the-art unsupervised methods, with a very limited subset of features. The approach proves promise to treat with very broad domains.

Thermodynamic limit of random partitions and dispersionless Toda hierarchy

NASA Astrophysics Data System (ADS)

Takasaki, Kanehisa; Nakatsu, Toshio

2012-01-01

We study the thermodynamic limit of random partition models for the instanton sum of 4D and 5D supersymmetric U(1) gauge theories deformed by some physical observables. The physical observables correspond to external potentials in the statistical model. The partition function is reformulated in terms of the density function of Maya diagrams. The thermodynamic limit is governed by a limit shape of Young diagrams associated with dominant terms in the partition function. The limit shape is characterized by a variational problem, which is further converted to a scalar-valued Riemann-Hilbert problem. This Riemann-Hilbert problem is solved with the aid of a complex curve, which may be thought of as the Seiberg-Witten curve of the deformed U(1) gauge theory. This solution of the Riemann-Hilbert problem is identified with a special solution of the dispersionless Toda hierarchy that satisfies a pair of generalized string equations. The generalized string equations for the 5D gauge theory are shown to be related to hidden symmetries of the statistical model. The prepotential and the Seiberg-Witten differential are also considered.

A Locally Optimal Algorithm for Estimating a Generating Partition from an Observed Time Series and Its Application to Anomaly Detection.

PubMed

Ghalyan, Najah F; Miller, David J; Ray, Asok

2018-06-12

Estimation of a generating partition is critical for symbolization of measurements from discrete-time dynamical systems, where a sequence of symbols from a (finite-cardinality) alphabet may uniquely specify the underlying time series. Such symbolization is useful for computing measures (e.g., Kolmogorov-Sinai entropy) to identify or characterize the (possibly unknown) dynamical system. It is also useful for time series classification and anomaly detection. The seminal work of Hirata, Judd, and Kilminster (2004) derives a novel objective function, akin to a clustering objective, that measures the discrepancy between a set of reconstruction values and the points from the time series. They cast estimation of a generating partition via the minimization of their objective function. Unfortunately, their proposed algorithm is nonconvergent, with no guarantee of finding even locally optimal solutions with respect to their objective. The difficulty is a heuristic-nearest neighbor symbol assignment step. Alternatively, we develop a novel, locally optimal algorithm for their objective. We apply iterative nearest-neighbor symbol assignments with guaranteed discrepancy descent, by which joint, locally optimal symbolization of the entire time series is achieved. While most previous approaches frame generating partition estimation as a state-space partitioning problem, we recognize that minimizing the Hirata et al. (2004) objective function does not induce an explicit partitioning of the state space, but rather the space consisting of the entire time series (effectively, clustering in a (countably) infinite-dimensional space). Our approach also amounts to a novel type of sliding block lossy source coding. Improvement, with respect to several measures, is demonstrated over popular methods for symbolizing chaotic maps. We also apply our approach to time-series anomaly detection, considering both chaotic maps and failure application in a polycrystalline alloy material.

On the estimation of the domain of attraction for discrete-time switched and hybrid nonlinear systems

NASA Astrophysics Data System (ADS)

Kit Luk, Chuen; Chesi, Graziano

2015-11-01

This paper addresses the estimation of the domain of attraction for discrete-time nonlinear systems where the vector field is subject to changes. First, the paper considers the case of switched systems, where the vector field is allowed to arbitrarily switch among the elements of a finite family. Second, the paper considers the case of hybrid systems, where the state space is partitioned into several regions described by polynomial inequalities, and the vector field is defined on each region independently from the other ones. In both cases, the problem consists of computing the largest sublevel set of a Lyapunov function included in the domain of attraction. An approach is proposed for solving this problem based on convex programming, which provides a guaranteed inner estimate of the sought sublevel set. The conservatism of the provided estimate can be decreased by increasing the size of the optimisation problem. Some numerical examples illustrate the proposed approach.

Multilevel Green's function interpolation method for scattering from composite metallic and dielectric objects.

PubMed

Shi, Yan; Wang, Hao Gang; Li, Long; Chan, Chi Hou

2008-10-01

A multilevel Green's function interpolation method based on two kinds of multilevel partitioning schemes--the quasi-2D and the hybrid partitioning scheme--is proposed for analyzing electromagnetic scattering from objects comprising both conducting and dielectric parts. The problem is formulated using the surface integral equation for homogeneous dielectric and conducting bodies. A quasi-2D multilevel partitioning scheme is devised to improve the efficiency of the Green's function interpolation. In contrast to previous multilevel partitioning schemes, noncubic groups are introduced to discretize the whole EM structure in this quasi-2D multilevel partitioning scheme. Based on the detailed analysis of the dimension of the group in this partitioning scheme, a hybrid quasi-2D/3D multilevel partitioning scheme is proposed to effectively handle objects with fine local structures. Selection criteria for some key parameters relating to the interpolation technique are given. The proposed algorithm is ideal for the solution of problems involving objects such as missiles, microstrip antenna arrays, photonic bandgap structures, etc. Numerical examples are presented to show that CPU time is between O(N) and O(N log N) while the computer memory requirement is O(N).

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Some controversial multiple testing problems in regulatory applications.

PubMed

Hung, H M James; Wang, Sue-Jane

2009-01-01

Multiple testing problems in regulatory applications are often more challenging than the problems of handling a set of mathematical symbols representing multiple null hypotheses under testing. In the union-intersection setting, it is important to define a family of null hypotheses relevant to the clinical questions at issue. The distinction between primary endpoint and secondary endpoint needs to be considered properly in different clinical applications. Without proper consideration, the widely used sequential gate keeping strategies often impose too many logical restrictions to make sense, particularly to deal with the problem of testing multiple doses and multiple endpoints, the problem of testing a composite endpoint and its component endpoints, and the problem of testing superiority and noninferiority in the presence of multiple endpoints. Partitioning the null hypotheses involved in closed testing into clinical relevant orderings or sets can be a viable alternative to resolving the illogical problems requiring more attention from clinical trialists in defining the clinical hypotheses or clinical question(s) at the design stage. In the intersection-union setting there is little room for alleviating the stringency of the requirement that each endpoint must meet the same intended alpha level, unless the parameter space under the null hypothesis can be substantially restricted. Such restriction often requires insurmountable justification and usually cannot be supported by the internal data. Thus, a possible remedial approach to alleviate the possible conservatism as a result of this requirement is a group-sequential design strategy that starts with a conservative sample size planning and then utilizes an alpha spending function to possibly reach the conclusion early.

Spatial partitioning algorithms for data visualization

NASA Astrophysics Data System (ADS)

Devulapalli, Raghuveer; Quist, Mikael; Carlsson, John Gunnar

2013-12-01

Spatial partitions of an information space are frequently used for data visualization. Weighted Voronoi diagrams are among the most popular ways of dividing a space into partitions. However, the problem of computing such a partition efficiently can be challenging. For example, a natural objective is to select the weights so as to force each Voronoi region to take on a pre-defined area, which might represent the relevance or market share of an informational object. In this paper, we present an easy and fast algorithm to compute these weights of the Voronoi diagrams. Unlike previous approaches whose convergence properties are not well-understood, we give a formulation to the problem based on convex optimization with excellent performance guarantees in theory and practice. We also show how our technique can be used to control the shape of these partitions. More specifically we show how to convert undesirable skinny and long regions into fat regions while maintaining the areas of the partitions. As an application, we use these to visualize the amount of website traffic for the top 101 websites.

Application of controller partitioning optimization procedure to integrated flight/propulsion control design for a STOVL aircraft

NASA Technical Reports Server (NTRS)

Garg, Sanjay; Schmidt, Phillip H.

1993-01-01

A parameter optimization framework has earlier been developed to solve the problem of partitioning a centralized controller into a decentralized, hierarchical structure suitable for integrated flight/propulsion control implementation. This paper presents results from the application of the controller partitioning optimization procedure to IFPC design for a Short Take-Off and Vertical Landing (STOVL) aircraft in transition flight. The controller partitioning problem and the parameter optimization algorithm are briefly described. Insight is provided into choosing various 'user' selected parameters in the optimization cost function such that the resulting optimized subcontrollers will meet the characteristics of the centralized controller that are crucial to achieving the desired closed-loop performance and robustness, while maintaining the desired subcontroller structure constraints that are crucial for IFPC implementation. The optimization procedure is shown to improve upon the initial partitioned subcontrollers and lead to performance comparable to that achieved with the centralized controller. This application also provides insight into the issues that should be addressed at the centralized control design level in order to obtain implementable partitioned subcontrollers.

FPFH-based graph matching for 3D point cloud registration

NASA Astrophysics Data System (ADS)

Zhao, Jiapeng; Li, Chen; Tian, Lihua; Zhu, Jihua

2018-04-01

Correspondence detection is a vital step in point cloud registration and it can help getting a reliable initial alignment. In this paper, we put forward an advanced point feature-based graph matching algorithm to solve the initial alignment problem of rigid 3D point cloud registration with partial overlap. Specifically, Fast Point Feature Histograms are used to determine the initial possible correspondences firstly. Next, a new objective function is provided to make the graph matching more suitable for partially overlapping point cloud. The objective function is optimized by the simulated annealing algorithm for final group of correct correspondences. Finally, we present a novel set partitioning method which can transform the NP-hard optimization problem into a O(n3)-solvable one. Experiments on the Stanford and UWA public data sets indicates that our method can obtain better result in terms of both accuracy and time cost compared with other point cloud registration methods.

An impatient evolutionary algorithm with probabilistic tabu search for unified solution of some NP-hard problems in graph and set theory via clique finding.

PubMed

Guturu, Parthasarathy; Dantu, Ram

2008-06-01

Many graph- and set-theoretic problems, because of their tremendous application potential and theoretical appeal, have been well investigated by the researchers in complexity theory and were found to be NP-hard. Since the combinatorial complexity of these problems does not permit exhaustive searches for optimal solutions, only near-optimal solutions can be explored using either various problem-specific heuristic strategies or metaheuristic global-optimization methods, such as simulated annealing, genetic algorithms, etc. In this paper, we propose a unified evolutionary algorithm (EA) to the problems of maximum clique finding, maximum independent set, minimum vertex cover, subgraph and double subgraph isomorphism, set packing, set partitioning, and set cover. In the proposed approach, we first map these problems onto the maximum clique-finding problem (MCP), which is later solved using an evolutionary strategy. The proposed impatient EA with probabilistic tabu search (IEA-PTS) for the MCP integrates the best features of earlier successful approaches with a number of new heuristics that we developed to yield a performance that advances the state of the art in EAs for the exploration of the maximum cliques in a graph. Results of experimentation with the 37 DIMACS benchmark graphs and comparative analyses with six state-of-the-art algorithms, including two from the smaller EA community and four from the larger metaheuristics community, indicate that the IEA-PTS outperforms the EAs with respect to a Pareto-lexicographic ranking criterion and offers competitive performance on some graph instances when individually compared to the other heuristic algorithms. It has also successfully set a new benchmark on one graph instance. On another benchmark suite called Benchmarks with Hidden Optimal Solutions, IEA-PTS ranks second, after a very recent algorithm called COVER, among its peers that have experimented with this suite.

Trace element partitioning between plagioclase and melt: An investigation of the impact of experimental and analytical procedures

NASA Astrophysics Data System (ADS)

Nielsen, Roger L.; Ustunisik, Gokce; Weinsteiger, Allison B.; Tepley, Frank J.; Johnston, A. Dana; Kent, Adam J. R.

2017-09-01

Quantitative models of petrologic processes require accurate partition coefficients. Our ability to obtain accurate partition coefficients is constrained by their dependence on pressure temperature and composition, and on the experimental and analytical techniques we apply. The source and magnitude of error in experimental studies of trace element partitioning may go unrecognized if one examines only the processed published data. The most important sources of error are relict crystals, and analyses of more than one phase in the analytical volume. Because we have typically published averaged data, identification of compromised data is difficult if not impossible. We addressed this problem by examining unprocessed data from plagioclase/melt partitioning experiments, by comparing models based on that data with existing partitioning models, and evaluated the degree to which the partitioning models are dependent on the calibration data. We found that partitioning models are dependent on the calibration data in ways that result in erroneous model values, and that the error will be systematic and dependent on the value of the partition coefficient. In effect, use of different calibration datasets will result in partitioning models whose results are systematically biased, and that one can arrive at different and conflicting conclusions depending on how a model is calibrated, defeating the purpose of applying the models. Ultimately this is an experimental data problem, which can be solved if we publish individual analyses (not averages) or use a projection method wherein we use an independent compositional constraint to identify and estimate the uncontaminated composition of each phase.

Clustering Qualitative Data Based on Binary Equivalence Relations: Neighborhood Search Heuristics for the Clique Partitioning Problem

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich

2009-01-01

The clique partitioning problem (CPP) requires the establishment of an equivalence relation for the vertices of a graph such that the sum of the edge costs associated with the relation is minimized. The CPP has important applications for the social sciences because it provides a framework for clustering objects measured on a collection of nominal…

Combining Techniques to Refine Item to Skills Q-Matrices with a Partition Tree

ERIC Educational Resources Information Center

Desmarais, Michel C.; Xu, Peng; Beheshti, Behzad

2015-01-01

The problem of mapping items to skills is gaining interest with the emergence of recent techniques that can use data for both defining this mapping, and for refining mappings given by experts. We investigate the problem of refining mapping from an expert by combining the output of different techniques. The combination is based on a partition tree…

Fully polynomial-time approximation scheme for a special case of a quadratic Euclidean 2-clustering problem

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Khandeev, V. I.

2016-02-01

The strongly NP-hard problem of partitioning a finite set of points of Euclidean space into two clusters of given sizes (cardinalities) minimizing the sum (over both clusters) of the intracluster sums of squared distances from the elements of the clusters to their centers is considered. It is assumed that the center of one of the sought clusters is specified at the desired (arbitrary) point of space (without loss of generality, at the origin), while the center of the other one is unknown and determined as the mean value over all elements of this cluster. It is shown that unless P = NP, there is no fully polynomial-time approximation scheme for this problem, and such a scheme is substantiated in the case of a fixed space dimension.

Distribution-Preserving Stratified Sampling for Learning Problems.

PubMed

Cervellera, Cristiano; Maccio, Danilo

2017-06-09

The need for extracting a small sample from a large amount of real data, possibly streaming, arises routinely in learning problems, e.g., for storage, to cope with computational limitations, obtain good training/test/validation sets, and select minibatches for stochastic gradient neural network training. Unless we have reasons to select the samples in an active way dictated by the specific task and/or model at hand, it is important that the distribution of the selected points is as similar as possible to the original data. This is obvious for unsupervised learning problems, where the goal is to gain insights on the distribution of the data, but it is also relevant for supervised problems, where the theory explains how the training set distribution influences the generalization error. In this paper, we analyze the technique of stratified sampling from the point of view of distances between probabilities. This allows us to introduce an algorithm, based on recursive binary partition of the input space, aimed at obtaining samples that are distributed as much as possible as the original data. A theoretical analysis is proposed, proving the (greedy) optimality of the procedure together with explicit error bounds. An adaptive version of the algorithm is also introduced to cope with streaming data. Simulation tests on various data sets and different learning tasks are also provided.

A Sharp methodology for VLSI layout

NASA Astrophysics Data System (ADS)

Bapat, Shekhar

1993-01-01

The layout problem for VLSI circuits is recognized as a very difficult problem and has been traditionally decomposed into the several seemingly independent sub-problems of placement, global routing, and detailed routing. Although this structure achieves a reduction in programming complexity, it is also typically accompanied by a reduction in solution quality. Most current placement research recognizes that the separation is artificial, and that the placement and routing problems should be solved ideally in tandem. We propose a new interconnection model, Sharp and an associated partitioning algorithm. The Sharp interconnection model uses a partitioning shape that roughly resembles the musical sharp 'number sign' and makes extensive use of pre-computed rectilinear Steiner trees. The model is designed to generate strategic routing information along with the partitioning results. Additionally, the Sharp model also generates estimates of the routing congestion. We also propose the Sharp layout heuristic that solves the layout problem in its entirety. The Sharp layout heuristic makes extensive use of the Sharp partitioning model. The use of precomputed Steiner tree forms enables the method to model accurately net characteristics. For example, the Steiner tree forms can model both the length of the net and more importantly its route. In fact, the tree forms are also appropriate for modeling the timing delays of nets. The Sharp heuristic works to minimize both the total layout area by minimizing total net length (thus reducing the total wiring area), and the congestion imbalances in the various channels (thus reducing the unused or wasted channel area). Our heuristic uses circuit element movements amongst the different partitioning blocks and selection of alternate minimal Steiner tree forms to achieve this goal. The objective function for the algorithm can be modified readily to include other important circuit constraints like propagation delays. The layout technique first computes a very high-level approximation of the layout solution (i.e., the positions of the circuit elements and the associated net routes). The approximate solution is alternately refined, objective function. The technique creates well defined sub-problems and offers intermediary steps that can be solved in parallel, as well as a parallel mechanism to merge the sub-problem solutions.

Handling Data Skew in MapReduce Cluster by Using Partition Tuning

PubMed

Gao, Yufei; Zhou, Yanjie; Zhou, Bing; Shi, Lei; Zhang, Jiacai

2017-01-01

The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data. © 2017 Yufei Gao et al.

Handling Data Skew in MapReduce Cluster by Using Partition Tuning.

PubMed

Gao, Yufei; Zhou, Yanjie; Zhou, Bing; Shi, Lei; Zhang, Jiacai

2017-01-01

The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data.

Handling Data Skew in MapReduce Cluster by Using Partition Tuning

PubMed Central

Zhou, Yanjie; Zhou, Bing; Shi, Lei

2017-01-01

The healthcare industry has generated large amounts of data, and analyzing these has emerged as an important problem in recent years. The MapReduce programming model has been successfully used for big data analytics. However, data skew invariably occurs in big data analytics and seriously affects efficiency. To overcome the data skew problem in MapReduce, we have in the past proposed a data processing algorithm called Partition Tuning-based Skew Handling (PTSH). In comparison with the one-stage partitioning strategy used in the traditional MapReduce model, PTSH uses a two-stage strategy and the partition tuning method to disperse key-value pairs in virtual partitions and recombines each partition in case of data skew. The robustness and efficiency of the proposed algorithm were tested on a wide variety of simulated datasets and real healthcare datasets. The results showed that PTSH algorithm can handle data skew in MapReduce efficiently and improve the performance of MapReduce jobs in comparison with the native Hadoop, Closer, and locality-aware and fairness-aware key partitioning (LEEN). We also found that the time needed for rule extraction can be reduced significantly by adopting the PTSH algorithm, since it is more suitable for association rule mining (ARM) on healthcare data. PMID:29065568

Partitioning Strategy Using Static Analysis Techniques

NASA Astrophysics Data System (ADS)

Seo, Yongjin; Soo Kim, Hyeon

2016-08-01

Flight software is software used in satellites' on-board computers. It has requirements such as real time and reliability. The IMA architecture is used to satisfy these requirements. The IMA architecture has the concept of partitions and this affected the configuration of flight software. That is, situations occurred in which software that had been loaded on one system was divided into many partitions when being loaded. For new issues, existing studies use experience based partitioning methods. However, these methods have a problem that they cannot be reused. In this respect, this paper proposes a partitioning method that is reusable and consistent.

New Linear Partitioning Models Based on Experimental Water: Supercritical CO2 Partitioning Data of Selected Organic Compounds.

PubMed

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V; Karamalidis, Athanasios K

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch-reactor system with dual spectroscopic detectors: a near-infrared spectrometer for measuring the organic analyte in the CO2 phase and a UV detector for quantifying the analyte in the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly parameter linear free-energy relationship and to develop five new linear free-energy relationships for predicting water-sc-CO2 partitioning coefficients. A total of four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than does the model built for the entire data set.

Cell-autonomous-like silencing of GFP-partitioned transgenic Nicotiana benthamiana.

PubMed

Sohn, Seong-Han; Frost, Jennifer; Kim, Yoon-Hee; Choi, Seung-Kook; Lee, Yi; Seo, Mi-Suk; Lim, Sun-Hyung; Choi, Yeonhee; Kim, Kook-Hyung; Lomonossoff, George

2014-08-01

We previously reported the novel partitioning of regional GFP-silencing on leaves of 35S-GFP transgenic plants, coining the term "partitioned silencing". We set out to delineate the mechanism of partitioned silencing. Here, we report that the partitioned plants were hemizygous for the transgene, possessing two direct-repeat copies of 35S-GFP. The detection of both siRNA expression (21 and 24 nt) and DNA methylation enrichment specifically at silenced regions indicated that both post-transcriptional gene silencing (PTGS) and transcriptional gene silencing (TGS) were involved in the silencing mechanism. Using in vivo agroinfiltration of 35S-GFP/GUS and inoculation of TMV-GFP RNA, we demonstrate that PTGS, not TGS, plays a dominant role in the partitioned silencing, concluding that the underlying mechanism of partitioned silencing is analogous to RNA-directed DNA methylation (RdDM). The initial pattern of partitioned silencing was tightly maintained in a cell-autonomous manner, although partitioned-silenced regions possess a potential for systemic spread. Surprisingly, transcriptome profiling through next-generation sequencing demonstrated that expression levels of most genes involved in the silencing pathway were similar in both GFP-expressing and silenced regions although a diverse set of region-specific transcripts were detected.This suggests that partitioned silencing can be triggered and regulated by genes other than the genes involved in the silencing pathway. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Mg-perovskite/silicate melt and magnesiowuestite/silicate melt partition coefficients for KLB-1 at 250 Kbars

NASA Technical Reports Server (NTRS)

Drake, Michael J.; Rubie, David C.; Mcfarlane, Elisabeth A.

1992-01-01

The partitioning of elements amongst lower mantle phases and silicate melts is of interest in unraveling the early thermal history of the Earth. Because of the technical difficulty in carrying out such measurements, only one direct set of measurements was reported previously, and these results as well as interpretations based on them have generated controversy. Here we report what are to our knowledge only the second set of directly measured trace element partition coefficients for a natural system (KLB-1).

Matrix partitioning and EOF/principal component analysis of Antarctic Sea ice brightness temperatures

NASA Technical Reports Server (NTRS)

Murray, C. W., Jr.; Mueller, J. L.; Zwally, H. J.

1984-01-01

A field of measured anomalies of some physical variable relative to their time averages, is partitioned in either the space domain or the time domain. Eigenvectors and corresponding principal components of the smaller dimensioned covariance matrices associated with the partitioned data sets are calculated independently, then joined to approximate the eigenstructure of the larger covariance matrix associated with the unpartitioned data set. The accuracy of the approximation (fraction of the total variance in the field) and the magnitudes of the largest eigenvalues from the partitioned covariance matrices together determine the number of local EOF's and principal components to be joined by any particular level. The space-time distribution of Nimbus-5 ESMR sea ice measurement is analyzed.

Anionic Pt in Silicate Melts at Low Oxygen Fugacity: Speciation, Partitioning and Implications for Core Formation Processes on Asteroids

NASA Technical Reports Server (NTRS)

Medard, E.; Martin, A. M.; Righter, K.; Malouta, A.; Lee, C.-T.

2017-01-01

Most siderophile element concentrations in planetary mantles can be explained by metal/ silicate equilibration at high temperature and pressure during core formation. Highly siderophile elements (HSE = Au, Re, and the Pt-group elements), however, usually have higher mantle abundances than predicted by partitioning models, suggesting that their concentrations have been set by late accretion of material that did not equilibrate with the core. The partitioning of HSE at the low oxygen fugacities relevant for core formation is however poorly constrained due to the lack of sufficient experimental constraints to describe the variations of partitioning with key variables like temperature, pressure, and oxygen fugacity. To better understand the relative roles of metal/silicate partitioning and late accretion, we performed a self-consistent set of experiments that parameterizes the influence of oxygen fugacity, temperature and melt composition on the partitioning of Pt, one of the HSE, between metal and silicate melts. The major outcome of this project is the fact that Pt dissolves in an anionic form in silicate melts, causing a dependence of partitioning on oxygen fugacity opposite to that reported in previous studies.

Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

NASA Astrophysics Data System (ADS)

Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

2010-12-01

Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem models.

Partition coefficients of organic compounds between water and imidazolium-, pyridinium-, and phosphonium-based ionic liquids.

PubMed

Padró, Juan M; Pellegrino Vidal, Rocío B; Reta, Mario

2014-12-01

The partition coefficients, P IL/w, of several compounds, some of them of biological and pharmacological interest, between water and room-temperature ionic liquids based on the imidazolium, pyridinium, and phosphonium cations, namely 1-octyl-3-methylimidazolium hexafluorophosphate, N-octylpyridinium tetrafluorophosphate, trihexyl(tetradecyl)phosphonium chloride, trihexyl(tetradecyl)phosphonium bromide, trihexyl(tetradecyl)phosphonium bis(trifluoromethylsulfonyl)imide, and trihexyl(tetradecyl)phosphonium dicyanamide, were accurately measured. In this way, we extended our database of partition coefficients in room-temperature ionic liquids previously reported. We employed the solvation parameter model with different probe molecules (the training set) to elucidate the chemical interactions involved in the partition process and discussed the most relevant differences among the three types of ionic liquids. The multiparametric equations obtained with the aforementioned model were used to predict the partition coefficients for compounds (the test set) not present in the training set, most being of biological and pharmacological interest. An excellent agreement between calculated and experimental log P IL/w values was obtained. Thus, the obtained equations can be used to predict, a priori, the extraction efficiency for any compound using these ionic liquids as extraction solvents in liquid-liquid extractions.

Balancing a U-Shaped Assembly Line by Applying Nested Partitions Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhagwat, Nikhil V.

2005-01-01

In this study, we applied the Nested Partitions method to a U-line balancing problem and conducted experiments to evaluate the application. From the results, it is quite evident that the Nested Partitions method provided near optimal solutions (optimal in some cases). Besides, the execution time is quite short as compared to the Branch and Bound algorithm. However, for larger data sets, the algorithm took significantly longer times for execution. One of the reasons could be the way in which the random samples are generated. In the present study, a random sample is a solution in itself which requires assignment ofmore » tasks to various stations. The time taken to assign tasks to stations is directly proportional to the number of tasks. Thus, if the number of tasks increases, the time taken to generate random samples for the different regions also increases. The performance index for the Nested Partitions method in the present study was the number of stations in the random solutions (samples) generated. The total idle time for the samples can be used as another performance index. ULINO method is known to have used a combination of bounds to come up with good solutions. This approach of combining different performance indices can be used to evaluate the random samples and obtain even better solutions. Here, we used deterministic time values for the tasks. In industries where majority of tasks are performed manually, the stochastic version of the problem could be of vital importance. Experimenting with different objective functions (No. of stations was used in this study) could be of some significance to some industries where in the cost associated with creation of a new station is not the same. For such industries, the results obtained by using the present approach will not be of much value. Labor costs, task incompletion costs or a combination of those can be effectively used as alternate objective functions.« less

Hybrid Discrete-Continuous Markov Decision Processes

NASA Technical Reports Server (NTRS)

Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich

2003-01-01

This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.

Dynamically allocating sets of fine-grained processors to running computations

NASA Technical Reports Server (NTRS)

Middleton, David

1988-01-01

Researchers explore an approach to using general purpose parallel computers which involves mapping hardware resources onto computations instead of mapping computations onto hardware. Problems such as processor allocation, task scheduling and load balancing, which have traditionally proven to be challenging, change significantly under this approach and may become amenable to new attacks. Researchers describe the implementation of this approach used by the FFP Machine whose computation and communication resources are repeatedly partitioned into disjoint groups that match the needs of available tasks from moment to moment. Several consequences of this system are examined.

The Partition of Multi-Resolution LOD Based on Qtm

NASA Astrophysics Data System (ADS)

Hou, M.-L.; Xing, H.-Q.; Zhao, X.-S.; Chen, J.

2011-08-01

The partition hierarch of Quaternary Triangular Mesh (QTM) determine the accuracy of spatial analysis and application based on QTM. In order to resolve the problem that the partition hierarch of QTM is limited by the level of the computer hardware, the new method that Multi- Resolution LOD (Level of Details) based on QTM will be discussed in this paper. This method can make the resolution of the cells varying with the viewpoint position by partitioning the cells of QTM, selecting the particular area according to the viewpoint; dealing with the cracks caused by different subdivisions, it satisfies the request of unlimited partition in part.

The iron-nickel-phosphorus system: Effects on the distribution of trace elements during the evolution of iron meteorites

NASA Astrophysics Data System (ADS)

Corrigan, Catherine M.; Chabot, Nancy L.; McCoy, Timothy J.; McDonough, William F.; Watson, Heather C.; Saslow, Sarah A.; Ash, Richard D.

2009-05-01

To better understand the partitioning behavior of elements during the formation and evolution of iron meteorites, two sets of experiments were conducted at 1 atm in the Fe-Ni-P system. The first set examined the effect of P on solid metal/liquid metal partitioning behavior of 22 elements, while the other set explored the effect of the crystal structures of body-centered cubic (α)- and face-centered cubic (γ)-solid Fe alloys on partitioning behavior. Overall, the effect of P on the partition coefficients for the majority of the elements was minimal. As, Au, Ga, Ge, Ir, Os, Pt, Re, and Sb showed slightly increasing partition coefficients with increasing P-content of the metallic liquid. Co, Cu, Pd, and Sn showed constant partition coefficients. Rh, Ru, W, and Mo showed phosphorophile (P-loving) tendencies. Parameterization models were applied to solid metal/liquid metal results for 12 elements. As, Au, Pt, and Re failed to match previous parameterization models, requiring the determination of separate parameters for the Fe-Ni-S and Fe-Ni-P systems. Experiments with coexisting α and γ Fe alloy solids produced partitioning ratios close to unity, indicating that an α versus γ Fe alloy crystal structure has only a minor influence on the partitioning behaviors of the trace element studied. A simple relationship between an element's natural crystal structure and its α/γ partitioning ratio was not observed. If an iron meteorite crystallizes from a single metallic liquid that contains both S and P, the effect of P on the distribution of elements between the crystallizing solids and the residual liquid will be minor in comparison to the effect of S. This indicates that to a first order, fractional crystallization models of the Fe-Ni-S-P system that do not take into account P are appropriate for interpreting the evolution of iron meteorites if the effects of S are appropriately included in the effort.

Spectral partitioning in equitable graphs.

PubMed

Barucca, Paolo

2017-06-01

Graph partitioning problems emerge in a wide variety of complex systems, ranging from biology to finance, but can be rigorously analyzed and solved only for a few graph ensembles. Here, an ensemble of equitable graphs, i.e., random graphs with a block-regular structure, is studied, for which analytical results can be obtained. In particular, the spectral density of this ensemble is computed exactly for a modular and bipartite structure. Kesten-McKay's law for random regular graphs is found analytically to apply also for modular and bipartite structures when blocks are homogeneous. An exact solution to graph partitioning for two equal-sized communities is proposed and verified numerically, and a conjecture on the absence of an efficient recovery detectability transition in equitable graphs is suggested. A final discussion summarizes results and outlines their relevance for the solution of graph partitioning problems in other graph ensembles, in particular for the study of detectability thresholds and resolution limits in stochastic block models.

Spectral partitioning in equitable graphs

NASA Astrophysics Data System (ADS)

Barucca, Paolo

2017-06-01

Graph partitioning problems emerge in a wide variety of complex systems, ranging from biology to finance, but can be rigorously analyzed and solved only for a few graph ensembles. Here, an ensemble of equitable graphs, i.e., random graphs with a block-regular structure, is studied, for which analytical results can be obtained. In particular, the spectral density of this ensemble is computed exactly for a modular and bipartite structure. Kesten-McKay's law for random regular graphs is found analytically to apply also for modular and bipartite structures when blocks are homogeneous. An exact solution to graph partitioning for two equal-sized communities is proposed and verified numerically, and a conjecture on the absence of an efficient recovery detectability transition in equitable graphs is suggested. A final discussion summarizes results and outlines their relevance for the solution of graph partitioning problems in other graph ensembles, in particular for the study of detectability thresholds and resolution limits in stochastic block models.

The photochemical formation and gas-particle partitioning of oxidation products of decamethyl cyclopentasiloxane and decamethyl tetrasiloxane in the atmosphere

NASA Astrophysics Data System (ADS)

Chandramouli, Bharadwaj; Kamens, Richard M.

Decamethyl cyclopentasiloxane (D 5) and decamethyl tetrasiloxane (MD 2M) were injected into a smog chamber containing fine Arizona road dust particles (95% surface area <2.6 μM) and an urban smog atmosphere in the daytime. A photochemical reaction - gas-particle partitioning reaction scheme, was implemented to simulate the formation and gas-particle partitioning of hydroxyl oxidation products of D 5 and MD 2M. This scheme incorporated the reactions of D 5 and MD 2M into an existing urban smog chemical mechanism carbon bond IV and partitioned the products between gas and particle phase by treating gas-particle partitioning as a kinetic process and specifying an uptake and off-gassing rate. A photochemical model PKSS was used to simulate this set of reactions. A Langmuirian partitioning model was used to convert the measured and estimated mass-based partitioning coefficients ( KP) to a molar or volume-based form. The model simulations indicated that >99% of all product silanol formed in the gas-phase partition immediately to particle phase and the experimental data agreed with model predictions. One product, D 4TOH was observed and confirmed for the D 5 reaction and this system was modeled successfully. Experimental data was inadequate for MD 2M reaction products and it is likely that more than one product formed. The model set up a framework into which more reaction and partitioning steps can be easily added.

Gas-particle partitioning of semi-volatile organics on organic aerosols using a predictive activity coefficient model: analysis of the effects of parameter choices on model performance

NASA Astrophysics Data System (ADS)

Chandramouli, Bharadwaj; Jang, Myoseon; Kamens, Richard M.

The partitioning of a diverse set of semivolatile organic compounds (SOCs) on a variety of organic aerosols was studied using smog chamber experimental data. Existing data on the partitioning of SOCs on aerosols from wood combustion, diesel combustion, and the α-pinene-O 3 reaction was augmented by carrying out smog chamber partitioning experiments on aerosols from meat cooking, and catalyzed and uncatalyzed gasoline engine exhaust. Model compositions for aerosols from meat cooking and gasoline combustion emissions were used to calculate activity coefficients for the SOCs in the organic aerosols and the Pankow absorptive gas/particle partitioning model was used to calculate the partitioning coefficient Kp and quantitate the predictive improvements of using the activity coefficient. The slope of the log K p vs. log p L0 correlation for partitioning on aerosols from meat cooking improved from -0.81 to -0.94 after incorporation of activity coefficients iγ om. A stepwise regression analysis of the partitioning model revealed that for the data set used in this study, partitioning predictions on α-pinene-O 3 secondary aerosol and wood combustion aerosol showed statistically significant improvement after incorporation of iγ om, which can be attributed to their overall polarity. The partitioning model was sensitive to changes in aerosol composition when updated compositions for α-pinene-O 3 aerosol and wood combustion aerosol were used. The octanol-air partitioning coefficient's ( KOA) effectiveness as a partitioning correlator over a variety of aerosol types was evaluated. The slope of the log K p- log K OA correlation was not constant over the aerosol types and SOCs used in the study and the use of KOA for partitioning correlations can potentially lead to significant deviations, especially for polar aerosols.

Multiple Versus Single Set Validation of Multivariate Models to Avoid Mistakes.

PubMed

Harrington, Peter de Boves

2018-01-02

Validation of multivariate models is of current importance for a wide range of chemical applications. Although important, it is neglected. The common practice is to use a single external validation set for evaluation. This approach is deficient and may mislead investigators with results that are specific to the single validation set of data. In addition, no statistics are available regarding the precision of a derived figure of merit (FOM). A statistical approach using bootstrapped Latin partitions is advocated. This validation method makes an efficient use of the data because each object is used once for validation. It was reviewed a decade earlier but primarily for the optimization of chemometric models this review presents the reasons it should be used for generalized statistical validation. Average FOMs with confidence intervals are reported and powerful, matched-sample statistics may be applied for comparing models and methods. Examples demonstrate the problems with single validation sets.

Research on Crack Formation in Gypsum Partitions with Doorway by Means of FEM and Fracture Mechanics

NASA Astrophysics Data System (ADS)

Kania, Tomasz; Stawiski, Bohdan

2017-10-01

Cracking damage in non-loadbearing internal partition walls is a serious problem that frequently occurs in new buildings within the short term after putting them into service or even before completion of construction. Damage in partition walls is sometimes so great that they cannot be accepted by their occupiers. This problem was illustrated by the example of damage in a gypsum partition wall with doorway attributed to deflection of the slabs beneath and above it. In searching for the deflection which causes damage in masonry walls, fracture mechanics applied to the Finite Element Method (FEM) have been used. For a description of gypsum behaviour, the smeared cracking material model has been selected, where stresses are transferred across the narrowly opened crack until its width reaches the ultimate value. Cracks in the Finite Element models overlapped the real damage observed in the buildings. In order to avoid cracks under the deflection of large floor slabs, the model of a wall with reinforcement in the doorstep zone and a 40 mm thick elastic junction between the partition and ceiling has been analysed.

Towards Cohomology of Renormalization: Bigrading the Combinatorial Hopf Algebra of Rooted Trees

NASA Astrophysics Data System (ADS)

Broadhurst, D. J.; Kreimer, D.

The renormalization of quantum field theory twists the antipode of a noncocommutative Hopf algebra of rooted trees, decorated by an infinite set of primitive divergences. The Hopf algebra of undecorated rooted trees, ℌR, generated by a single primitive divergence, solves a universal problem in Hochschild cohomology. It has two nontrivial closed Hopf subalgebras: the cocommutative subalgebra ℌladder of pure ladder diagrams and the Connes-Moscovici noncocommutative subalgebra ℌCM of noncommutative geometry. These three Hopf algebras admit a bigrading by n, the number of nodes, and an index k that specifies the degree of primitivity. In each case, we use iterations of the relevant coproduct to compute the dimensions of subspaces with modest values of n and k and infer a simple generating procedure for the remainder. The results for ℌladder are familiar from the theory of partitions, while those for ℌCM involve novel transforms of partitions. Most beautiful is the bigrading of ℌR, the largest of the three. Thanks to Sloane's superseeker, we discovered that it saturates all possible inequalities. We prove this by using the universal Hochschild-closed one-cocycle B+, which plugs one set of divergences into another, and by generalizing the concept of natural growth beyond that entailed by the Connes-Moscovici case. We emphasize the yet greater challenge of handling the infinite set of decorations of realistic quantum field theory.

Finite element modeling of diffusion and partitioning in biological systems: the infinite composite medium problem.

PubMed

Missel, P J

2000-01-01

Four methods are proposed for modeling diffusion in heterogeneous media where diffusion and partition coefficients take on differing values in each subregion. The exercise was conducted to validate finite element modeling (FEM) procedures in anticipation of modeling drug diffusion with regional partitioning into ocular tissue, though the approach can be useful for other organs, or for modeling diffusion in laminate devices. Partitioning creates a discontinuous value in the dependent variable (concentration) at an intertissue boundary that is not easily handled by available general-purpose FEM codes, which allow for only one value at each node. The discontinuity is handled using a transformation on the dependent variable based upon the region-specific partition coefficient. Methods were evaluated by their ability to reproduce a known exact result, for the problem of the infinite composite medium (Crank, J. The Mathematics of Diffusion, 2nd ed. New York: Oxford University Press, 1975, pp. 38-39.). The most physically intuitive method is based upon the concept of chemical potential, which is continuous across an interphase boundary (method III). This method makes the equation of the dependent variable highly nonlinear. This can be linearized easily by a change of variables (method IV). Results are also given for a one-dimensional problem simulating bolus injection into the vitreous, predicting time disposition of drug in vitreous and retina.

Solving multiconstraint assignment problems using learning automata.

PubMed

Horn, Geir; Oommen, B John

2010-02-01

This paper considers the NP-hard problem of object assignment with respect to multiple constraints: assigning a set of elements (or objects) into mutually exclusive classes (or groups), where the elements which are "similar" to each other are hopefully located in the same class. The literature reports solutions in which the similarity constraint consists of a single index that is inappropriate for the type of multiconstraint problems considered here and where the constraints could simultaneously be contradictory. This feature, where we permit possibly contradictory constraints, distinguishes this paper from the state of the art. Indeed, we are aware of no learning automata (or other heuristic) solutions which solve this problem in its most general setting. Such a scenario is illustrated with the static mapping problem, which consists of distributing the processes of a parallel application onto a set of computing nodes. This is a classical and yet very important problem within the areas of parallel computing, grid computing, and cloud computing. We have developed four learning-automata (LA)-based algorithms to solve this problem: First, a fixed-structure stochastic automata algorithm is presented, where the processes try to form pairs to go onto the same node. This algorithm solves the problem, although it requires some centralized coordination. As it is desirable to avoid centralized control, we subsequently present three different variable-structure stochastic automata (VSSA) algorithms, which have superior partitioning properties in certain settings, although they forfeit some of the scalability features of the fixed-structure algorithm. All three VSSA algorithms model the processes as automata having first the hosting nodes as possible actions; second, the processes as possible actions; and, third, attempting to estimate the process communication digraph prior to probabilistically mapping the processes. This paper, which, we believe, comprehensively reports the pioneering LA solutions to this problem, unequivocally demonstrates that LA can play an important role in solving complex combinatorial and integer optimization problems.

Distributed computing methodology for training neural networks in an image-guided diagnostic application.

PubMed

Plagianakos, V P; Magoulas, G D; Vrahatis, M N

2006-03-01

Distributed computing is a process through which a set of computers connected by a network is used collectively to solve a single problem. In this paper, we propose a distributed computing methodology for training neural networks for the detection of lesions in colonoscopy. Our approach is based on partitioning the training set across multiple processors using a parallel virtual machine. In this way, interconnected computers of varied architectures can be used for the distributed evaluation of the error function and gradient values, and, thus, training neural networks utilizing various learning methods. The proposed methodology has large granularity and low synchronization, and has been implemented and tested. Our results indicate that the parallel virtual machine implementation of the training algorithms developed leads to considerable speedup, especially when large network architectures and training sets are used.

The Application of the Weighted k-Partite Graph Problem to the Multiple Alignment for Metabolic Pathways.

PubMed

Chen, Wenbin; Hendrix, William; Samatova, Nagiza F

2017-12-01

The problem of aligning multiple metabolic pathways is one of very challenging problems in computational biology. A metabolic pathway consists of three types of entities: reactions, compounds, and enzymes. Based on similarities between enzymes, Tohsato et al. gave an algorithm for aligning multiple metabolic pathways. However, the algorithm given by Tohsato et al. neglects the similarities among reactions, compounds, enzymes, and pathway topology. How to design algorithms for the alignment problem of multiple metabolic pathways based on the similarity of reactions, compounds, and enzymes? It is a difficult computational problem. In this article, we propose an algorithm for the problem of aligning multiple metabolic pathways based on the similarities among reactions, compounds, enzymes, and pathway topology. First, we compute a weight between each pair of like entities in different input pathways based on the entities' similarity score and topological structure using Ay et al.'s methods. We then construct a weighted k-partite graph for the reactions, compounds, and enzymes. We extract a mapping between these entities by solving the maximum-weighted k-partite matching problem by applying a novel heuristic algorithm. By analyzing the alignment results of multiple pathways in different organisms, we show that the alignments found by our algorithm correctly identify common subnetworks among multiple pathways.

A Colorful Laboratory Investigation of Hydrophobic Interactions, the Partition Coefficient, Gibbs Energy of Transfer, and the Effect of Hofmeister Salts

ERIC Educational Resources Information Center

McCain, Daniel F.; Allgood, Ottie E.; Cox, Jacob T.; Falconi, Audrey E.; Kim, Michael J.; Shih, Wei-Yu

2012-01-01

Only a few pedagogical experiments have been published dealing specifically with the hydrophobic interaction though it plays a central role in biochemistry. A set of experiments is presented in which students partition a variety of colorful indicator dyes in biphasic water/organic solvent mixtures. Students monitor the partitioning visually and…

Lost in the supermarket: Quantifying the cost of partitioning memory sets in hybrid search.

PubMed

Boettcher, Sage E P; Drew, Trafton; Wolfe, Jeremy M

2018-01-01

The items on a memorized grocery list are not relevant in every aisle; for example, it is useless to search for the cabbage in the cereal aisle. It might be beneficial if one could mentally partition the list so only the relevant subset was active, so that vegetables would be activated in the produce section. In four experiments, we explored observers' abilities to partition memory searches. For example, if observers held 16 items in memory, but only eight of the items were relevant, would response times resemble a search through eight or 16 items? In Experiments 1a and 1b, observers were not faster for the partition set; however, they suffered relatively small deficits when "lures" (items from the irrelevant subset) were presented, indicating that they were aware of the partition. In Experiment 2 the partitions were based on semantic distinctions, and again, observers were unable to restrict search to the relevant items. In Experiments 3a and 3b, observers attempted to remove items from the list one trial at a time but did not speed up over the course of a block, indicating that they also could not limit their memory searches. Finally, Experiments 4a, 4b, 4c, and 4d showed that observers were able to limit their memory searches when a subset was relevant for a run of trials. Overall, observers appear to be unable or unwilling to partition memory sets from trial to trial, yet they are capable of restricting search to a memory subset that remains relevant for several trials. This pattern is consistent with a cost to switching between currently relevant memory items.

Comparative analysis of local spin definitions.

PubMed

Herrmann, Carmen; Reiher, Markus; Hess, Bernd A

2005-01-15

This work provides a survey of the definition of electron spin as a local property and its dependence on several parameters in actual calculations. We analyze one-determinant wave functions constructed from Hartree-Fock and, in particular, from Kohn-Sham orbitals within the collinear approach to electron spin. The scalar total spin operators S2 and Sz are partitioned by projection operators, as introduced by Clark and Davidson, in order to obtain local spin operators SASB and SzA, respectively. To complement the work of Davidson and co-workers, we analyze some features of local spins which have not yet been discussed in sufficient depth. The dependence of local spin on the choice of basis set, density functional, and projector is studied. We also discuss the results of Sz partitioning and show that SzA values depend less on these parameters than SASB values. Furthermore, we demonstrate that for small organic test molecules, a partitioning of Sz with preorthogonalized Lowdin projectors yields nearly the same results as one obtains using atoms-in-molecules projectors. In addition, the physical significance of nonzero SASB values for closed-shell molecules is investigated. It is shown that due to this problem, SASB values are useful for calculations of relative spin values, but not for absolute local spins, where SzA values appear to be better suited.

On the complexity of some quadratic Euclidean 2-clustering problems

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Pyatkin, A. V.

2016-03-01

Some problems of partitioning a finite set of points of Euclidean space into two clusters are considered. In these problems, the following criteria are minimized: (1) the sum over both clusters of the sums of squared pairwise distances between the elements of the cluster and (2) the sum of the (multiplied by the cardinalities of the clusters) sums of squared distances from the elements of the cluster to its geometric center, where the geometric center (or centroid) of a cluster is defined as the mean value of the elements in that cluster. Additionally, another problem close to (2) is considered, where the desired center of one of the clusters is given as input, while the center of the other cluster is unknown (is the variable to be optimized) as in problem (2). Two variants of the problems are analyzed, in which the cardinalities of the clusters are (1) parts of the input or (2) optimization variables. It is proved that all the considered problems are strongly NP-hard and that, in general, there is no fully polynomial-time approximation scheme for them (unless P = NP).

Partial Storage Optimization and Load Control Strategy of Cloud Data Centers

PubMed Central

2015-01-01

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner. PMID:25973444

Partial storage optimization and load control strategy of cloud data centers.

PubMed

Al Nuaimi, Klaithem; Mohamed, Nader; Al Nuaimi, Mariam; Al-Jaroodi, Jameela

2015-01-01

We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.

HARP: A Dynamic Inertial Spectral Partitioner

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Sohn, Andrew; Biswas, Rupak

1997-01-01

Partitioning unstructured graphs is central to the parallel solution of computational science and engineering problems. Spectral partitioners, such recursive spectral bisection (RSB), have proven effecfive in generating high-quality partitions of realistically-sized meshes. The major problem which hindered their wide-spread use was their long execution times. This paper presents a new inertial spectral partitioner, called HARP. The main objective of the proposed approach is to quickly partition the meshes at runtime in a manner that works efficiently for real applications in the context of distributed-memory machines. The underlying principle of HARP is to find the eigenvectors of the unpartitioned vertices and then project them onto the eigerivectors of the original mesh. Results for various meshes ranging in size from 1000 to 100,000 vertices indicate that HARP can indeed partition meshes rapidly at runtime. Experimental results show that our largest mesh can be partitioned sequentially in only a few seconds on an SP2 which is several times faster than other spectral partitioners while maintaining the solution quality of the proven RSB method. A parallel WI version of HARP has also been implemented on IBM SP2 and Cray T3E. Parallel HARP, running on 64 processors SP2 and T3E, can partition a mesh containing more than 100,000 vertices into 64 subgrids in about half a second. These results indicate that graph partitioning can now be truly embedded in dynamically-changing real-world applications.

Spatiotemporal motion boundary detection and motion boundary velocity estimation for tracking moving objects with a moving camera: a level sets PDEs approach with concurrent camera motion compensation.

PubMed

Feghali, Rosario; Mitiche, Amar

2004-11-01

The purpose of this study is to investigate a method of tracking moving objects with a moving camera. This method estimates simultaneously the motion induced by camera movement. The problem is formulated as a Bayesian motion-based partitioning problem in the spatiotemporal domain of the image quence. An energy functional is derived from the Bayesian formulation. The Euler-Lagrange descent equations determine imultaneously an estimate of the image motion field induced by camera motion and an estimate of the spatiotemporal motion undary surface. The Euler-Lagrange equation corresponding to the surface is expressed as a level-set partial differential equation for topology independence and numerically stable implementation. The method can be initialized simply and can track multiple objects with nonsimultaneous motions. Velocities on motion boundaries can be estimated from geometrical properties of the motion boundary. Several examples of experimental verification are given using synthetic and real-image sequences.

Comments on "The multisynapse neural network and its application to fuzzy clustering".

PubMed

Yu, Jian; Hao, Pengwei

2005-05-01

In the above-mentioned paper, Wei and Fahn proposed a neural architecture, the multisynapse neural network, to solve constrained optimization problems including high-order, logarithmic, and sinusoidal forms, etc. As one of its main applications, a fuzzy bidirectional associative clustering network (FBACN) was proposed for fuzzy-partition clustering according to the objective-functional method. The connection between the objective-functional-based fuzzy c-partition algorithms and FBACN is the Lagrange multiplier approach. Unfortunately, the Lagrange multiplier approach was incorrectly applied so that FBACN does not equivalently minimize its corresponding constrained objective-function. Additionally, Wei and Fahn adopted traditional definition of fuzzy c-partition, which is not satisfied by FBACN. Therefore, FBACN can not solve constrained optimization problems, either.

Hypergraph partitioning implementation for parallelizing matrix-vector multiplication using CUDA GPU-based parallel computing

NASA Astrophysics Data System (ADS)

Murni, Bustamam, A.; Ernastuti, Handhika, T.; Kerami, D.

2017-07-01

Calculation of the matrix-vector multiplication in the real-world problems often involves large matrix with arbitrary size. Therefore, parallelization is needed to speed up the calculation process that usually takes a long time. Graph partitioning techniques that have been discussed in the previous studies cannot be used to complete the parallelized calculation of matrix-vector multiplication with arbitrary size. This is due to the assumption of graph partitioning techniques that can only solve the square and symmetric matrix. Hypergraph partitioning techniques will overcome the shortcomings of the graph partitioning technique. This paper addresses the efficient parallelization of matrix-vector multiplication through hypergraph partitioning techniques using CUDA GPU-based parallel computing. CUDA (compute unified device architecture) is a parallel computing platform and programming model that was created by NVIDIA and implemented by the GPU (graphics processing unit).

High performance genetic algorithm for VLSI circuit partitioning

NASA Astrophysics Data System (ADS)

Dinu, Simona

2016-12-01

Partitioning is one of the biggest challenges in computer-aided design for VLSI circuits (very large-scale integrated circuits). This work address the min-cut balanced circuit partitioning problem- dividing the graph that models the circuit into almost equal sized k sub-graphs while minimizing the number of edges cut i.e. minimizing the number of edges connecting the sub-graphs. The problem may be formulated as a combinatorial optimization problem. Experimental studies in the literature have shown the problem to be NP-hard and thus it is important to design an efficient heuristic algorithm to solve it. The approach proposed in this study is a parallel implementation of a genetic algorithm, namely an island model. The information exchange between the evolving subpopulations is modeled using a fuzzy controller, which determines an optimal balance between exploration and exploitation of the solution space. The results of simulations show that the proposed algorithm outperforms the standard sequential genetic algorithm both in terms of solution quality and convergence speed. As a direction for future study, this research can be further extended to incorporate local search operators which should include problem-specific knowledge. In addition, the adaptive configuration of mutation and crossover rates is another guidance for future research.

GAS-PARTICLE PARTITIONING OF SEMI-VOLATILE ORGANICS ON ORGANIC AEROSOLS USING A PREDICTIVE ACTIVITY COEFFICIENT MODEL: ANALYSIS OF THE EFFECTS OF PARAMETER CHOICES ON MODEL PERFORMANCE. (R826771)

EPA Science Inventory

The partitioning of a diverse set of semivolatile organic compounds (SOCs) on a variety of organic aerosols was studied using smog chamber experimental data. Existing data on the partitioning of SOCs on aerosols from wood combustion, diesel combustion, and the Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators.

PubMed

Yin, Kedong; Yang, Benshuo; Li, Xuemei

2018-01-24

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making.

Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators

PubMed Central

Yin, Kedong; Yang, Benshuo

2018-01-01

In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making. PMID:29364849

Automatic partitioning of unstructured meshes for the parallel solution of problems in computational mechanics

NASA Technical Reports Server (NTRS)

Farhat, Charbel; Lesoinne, Michel

1993-01-01

Most of the recently proposed computational methods for solving partial differential equations on multiprocessor architectures stem from the 'divide and conquer' paradigm and involve some form of domain decomposition. For those methods which also require grids of points or patches of elements, it is often necessary to explicitly partition the underlying mesh, especially when working with local memory parallel processors. In this paper, a family of cost-effective algorithms for the automatic partitioning of arbitrary two- and three-dimensional finite element and finite difference meshes is presented and discussed in view of a domain decomposed solution procedure and parallel processing. The influence of the algorithmic aspects of a solution method (implicit/explicit computations), and the architectural specifics of a multiprocessor (SIMD/MIMD, startup/transmission time), on the design of a mesh partitioning algorithm are discussed. The impact of the partitioning strategy on load balancing, operation count, operator conditioning, rate of convergence and processor mapping is also addressed. Finally, the proposed mesh decomposition algorithms are demonstrated with realistic examples of finite element, finite volume, and finite difference meshes associated with the parallel solution of solid and fluid mechanics problems on the iPSC/2 and iPSC/860 multiprocessors.

Spectral methods in machine learning and new strategies for very large datasets

PubMed Central

Belabbas, Mohamed-Ali; Wolfe, Patrick J.

2009-01-01

Spectral methods are of fundamental importance in statistics and machine learning, because they underlie algorithms from classical principal components analysis to more recent approaches that exploit manifold structure. In most cases, the core technical problem can be reduced to computing a low-rank approximation to a positive-definite kernel. For the growing number of applications dealing with very large or high-dimensional datasets, however, the optimal approximation afforded by an exact spectral decomposition is too costly, because its complexity scales as the cube of either the number of training examples or their dimensionality. Motivated by such applications, we present here 2 new algorithms for the approximation of positive-semidefinite kernels, together with error bounds that improve on results in the literature. We approach this problem by seeking to determine, in an efficient manner, the most informative subset of our data relative to the kernel approximation task at hand. This leads to two new strategies based on the Nyström method that are directly applicable to massive datasets. The first of these—based on sampling—leads to a randomized algorithm whereupon the kernel induces a probability distribution on its set of partitions, whereas the latter approach—based on sorting—provides for the selection of a partition in a deterministic way. We detail their numerical implementation and provide simulation results for a variety of representative problems in statistical data analysis, each of which demonstrates the improved performance of our approach relative to existing methods. PMID:19129490

Independence polynomial and matching polynomial of the Koch network

NASA Astrophysics Data System (ADS)

Liao, Yunhua; Xie, Xiaoliang

2015-11-01

The lattice gas model and the monomer-dimer model are two classical models in statistical mechanics. It is well known that the partition functions of these two models are associated with the independence polynomial and the matching polynomial in graph theory, respectively. Both polynomials have been shown to belong to the “#P-complete” class, which indicate the problems are computationally “intractable”. We consider these two polynomials of the Koch networks which are scale-free with small-world effects. Explicit recurrences are derived, and explicit formulae are presented for the number of independent sets of a certain type.

Does History Repeat Itself? Wavelets and the Phylodynamics of Influenza A

PubMed Central

Tom, Jennifer A.; Sinsheimer, Janet S.; Suchard, Marc A.

2012-01-01

Unprecedented global surveillance of viruses will result in massive sequence data sets that require new statistical methods. These data sets press the limits of Bayesian phylogenetics as the high-dimensional parameters that comprise a phylogenetic tree increase the already sizable computational burden of these techniques. This burden often results in partitioning the data set, for example, by gene, and inferring the evolutionary dynamics of each partition independently, a compromise that results in stratified analyses that depend only on data within a given partition. However, parameter estimates inferred from these stratified models are likely strongly correlated, considering they rely on data from a single data set. To overcome this shortfall, we exploit the existing Monte Carlo realizations from stratified Bayesian analyses to efficiently estimate a nonparametric hierarchical wavelet-based model and learn about the time-varying parameters of effective population size that reflect levels of genetic diversity across all partitions simultaneously. Our methods are applied to complete genome influenza A sequences that span 13 years. We find that broad peaks and trends, as opposed to seasonal spikes, in the effective population size history distinguish individual segments from the complete genome. We also address hypotheses regarding intersegment dynamics within a formal statistical framework that accounts for correlation between segment-specific parameters. PMID:22160768

Generic pure quantum states as steady states of quasi-local dissipative dynamics

NASA Astrophysics Data System (ADS)

Karuvade, Salini; Johnson, Peter D.; Ticozzi, Francesco; Viola, Lorenza

2018-04-01

We investigate whether a generic pure state on a multipartite quantum system can be the unique asymptotic steady state of locality-constrained purely dissipative Markovian dynamics. In the tripartite setting, we show that the problem is equivalent to characterizing the solution space of a set of linear equations and establish that the set of pure states obeying the above property has either measure zero or measure one, solely depending on the subsystems’ dimension. A complete analytical characterization is given when the central subsystem is a qubit. In the N-partite case, we provide conditions on the subsystems’ size and the nature of the locality constraint, under which random pure states cannot be quasi-locally stabilized generically. Also, allowing for the possibility to approximately stabilize entangled pure states that cannot be exact steady states in settings where stabilizability is generic, our results offer insights into the extent to which random pure states may arise as unique ground states of frustration-free parent Hamiltonians. We further argue that, to a high probability, pure quantum states sampled from a t-design enjoy the same stabilizability properties of Haar-random ones as long as suitable dimension constraints are obeyed and t is sufficiently large. Lastly, we demonstrate a connection between the tasks of quasi-local state stabilization and unique state reconstruction from local tomographic information, and provide a constructive procedure for determining a generic N-partite pure state based only on knowledge of the support of any two of the reduced density matrices of about half the parties, improving over existing results.

Reconstruction of a piecewise constant conductivity on a polygonal partition via shape optimization in EIT

NASA Astrophysics Data System (ADS)

Beretta, Elena; Micheletti, Stefano; Perotto, Simona; Santacesaria, Matteo

2018-01-01

In this paper, we develop a shape optimization-based algorithm for the electrical impedance tomography (EIT) problem of determining a piecewise constant conductivity on a polygonal partition from boundary measurements. The key tool is to use a distributed shape derivative of a suitable cost functional with respect to movements of the partition. Numerical simulations showing the robustness and accuracy of the method are presented for simulated test cases in two dimensions.

Cost component analysis.

PubMed

Lörincz, András; Póczos, Barnabás

2003-06-01

In optimizations the dimension of the problem may severely, sometimes exponentially increase optimization time. Parametric function approximatiors (FAPPs) have been suggested to overcome this problem. Here, a novel FAPP, cost component analysis (CCA) is described. In CCA, the search space is resampled according to the Boltzmann distribution generated by the energy landscape. That is, CCA converts the optimization problem to density estimation. Structure of the induced density is searched by independent component analysis (ICA). The advantage of CCA is that each independent ICA component can be optimized separately. In turn, (i) CCA intends to partition the original problem into subproblems and (ii) separating (partitioning) the original optimization problem into subproblems may serve interpretation. Most importantly, (iii) CCA may give rise to high gains in optimization time. Numerical simulations illustrate the working of the algorithm.

Optimal partitioning of random programs across two processors

NASA Technical Reports Server (NTRS)

Nicol, D. M.

1986-01-01

The optimal partitioning of random distributed programs is discussed. It is concluded that the optimal partitioning of a homogeneous random program over a homogeneous distributed system either assigns all modules to a single processor, or distributes the modules as evenly as possible among all processors. The analysis rests heavily on the approximation which equates the expected maximum of a set of independent random variables with the set's maximum expectation. The results are strengthened by providing an approximation-free proof of this result for two processors under general conditions on the module execution time distribution. It is also shown that use of this approximation causes two of the previous central results to be false.

Predicting the partitioning of biological compounds between room-temperature ionic liquids and water by means of the solvation-parameter model.

PubMed

Padró, Juan M; Ponzinibbio, Agustín; Mesa, Leidy B Agudelo; Reta, Mario

2011-03-01

The partition coefficients, P(IL/w), for different probe molecules as well as for compounds of biological interest between the room-temperature ionic liquids (RTILs) 1-butyl-3-methylimidazolium hexafluorophosphate, [BMIM][PF(6)], 1-hexyl-3-methylimidazolium hexafluorophosphate, [HMIM][PF(6)], 1-octyl-3-methylimidazolium tetrafluoroborate, [OMIM][BF(4)] and water were accurately measured. [BMIM][PF(6)] and [OMIM][BF(4)] were synthesized by adapting a procedure from the literature to a simpler, single-vessel and faster methodology, with a much lesser consumption of organic solvent. We employed the solvation-parameter model to elucidate the general chemical interactions involved in RTIL/water partitioning. With this purpose, we have selected different solute descriptor parameters that measure polarity, polarizability, hydrogen-bond-donor and hydrogen-bond-acceptor interactions, and cavity formation for a set of specifically selected probe molecules (the training set). The obtained multiparametric equations were used to predict the partition coefficients for compounds not present in the training set (the test set), most being of biological interest. Partial solubility of the ionic liquid in water (and water into the ionic liquid) was taken into account to explain the obtained results. This fact has not been deeply considered up to date. Solute descriptors were obtained from the literature, when available, or else calculated through commercial software. An excellent agreement between calculated and experimental log P(IL/w) values was obtained, which demonstrated that the resulting multiparametric equations are robust and allow predicting partitioning for any organic molecule in the biphasic systems studied.

A distributed model predictive control scheme for leader-follower multi-agent systems

NASA Astrophysics Data System (ADS)

Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

2018-02-01

In this paper, we present a novel receding horizon control scheme for solving the formation problem of leader-follower configurations. The algorithm is based on set-theoretic ideas and is tuned for agents described by linear time-invariant (LTI) systems subject to input and state constraints. The novelty of the proposed framework relies on the capability to jointly use sequences of one-step controllable sets and polyhedral piecewise state-space partitions in order to online apply the 'better' control action in a distributed receding horizon fashion. Moreover, we prove that the design of both robust positively invariant sets and one-step-ahead controllable regions is achieved in a distributed sense. Simulations and numerical comparisons with respect to centralised and local-based strategies are finally performed on a group of mobile robots to demonstrate the effectiveness of the proposed control strategy.

Mode entanglement of Gaussian fermionic states

NASA Astrophysics Data System (ADS)

Spee, C.; Schwaiger, K.; Giedke, G.; Kraus, B.

2018-04-01

We investigate the entanglement of n -mode n -partite Gaussian fermionic states (GFS). First, we identify a reasonable definition of separability for GFS and derive a standard form for mixed states, to which any state can be mapped via Gaussian local unitaries (GLU). As the standard form is unique, two GFS are equivalent under GLU if and only if their standard forms coincide. Then, we investigate the important class of local operations assisted by classical communication (LOCC). These are central in entanglement theory as they allow one to partially order the entanglement contained in states. We show, however, that there are no nontrivial Gaussian LOCC (GLOCC) among pure n -partite (fully entangled) states. That is, any such GLOCC transformation can also be accomplished via GLU. To obtain further insight into the entanglement properties of such GFS, we investigate the richer class of Gaussian stochastic local operations assisted by classical communication (SLOCC). We characterize Gaussian SLOCC classes of pure n -mode n -partite states and derive them explicitly for few-mode states. Furthermore, we consider certain fermionic LOCC and show how to identify the maximally entangled set of pure n -mode n -partite GFS, i.e., the minimal set of states having the property that any other state can be obtained from one state inside this set via fermionic LOCC. We generalize these findings also to the pure m -mode n -partite (for m >n ) case.

A Very Large Area Network (VLAN) knowledge-base applied to space communication problems

NASA Technical Reports Server (NTRS)

Zander, Carol S.

1988-01-01

This paper first describes a hierarchical model for very large area networks (VLAN). Space communication problems whose solution could profit by the model are discussed and then an enhanced version of this model incorporating the knowledge needed for the missile detection-destruction problem is presented. A satellite network or VLAN is a network which includes at least one satellite. Due to the complexity, a compromise between fully centralized and fully distributed network management has been adopted. Network nodes are assigned to a physically localized group, called a partition. Partitions consist of groups of cell nodes with one cell node acting as the organizer or master, called the Group Master (GM). Coordinating the group masters is a Partition Master (PM). Knowledge is also distributed hierarchically existing in at least two nodes. Each satellite node has a back-up earth node. Knowledge must be distributed in such a way so as to minimize information loss when a node fails. Thus the model is hierarchical both physically and informationally.

Approximation algorithm for the problem of partitioning a sequence into clusters

NASA Astrophysics Data System (ADS)

Kel'manov, A. V.; Mikhailova, L. V.; Khamidullin, S. A.; Khandeev, V. I.

2017-08-01

We consider the problem of partitioning a finite sequence of Euclidean points into a given number of clusters (subsequences) using the criterion of the minimal sum (over all clusters) of intercluster sums of squared distances from the elements of the clusters to their centers. It is assumed that the center of one of the desired clusters is at the origin, while the center of each of the other clusters is unknown and determined as the mean value over all elements in this cluster. Additionally, the partition obeys two structural constraints on the indices of sequence elements contained in the clusters with unknown centers: (1) the concatenation of the indices of elements in these clusters is an increasing sequence, and (2) the difference between an index and the preceding one is bounded above and below by prescribed constants. It is shown that this problem is strongly NP-hard. A 2-approximation algorithm is constructed that is polynomial-time for a fixed number of clusters.

A dynamic re-partitioning strategy based on the distribution of key in Spark

NASA Astrophysics Data System (ADS)

Zhang, Tianyu; Lian, Xin

2018-05-01

Spark is a memory-based distributed data processing framework, has the ability of processing massive data and becomes a focus in Big Data. But the performance of Spark Shuffle depends on the distribution of data. The naive Hash partition function of Spark can not guarantee load balancing when data is skewed. The time of job is affected by the node which has more data to process. In order to handle this problem, dynamic sampling is used. In the process of task execution, histogram is used to count the key frequency distribution of each node, and then generate the global key frequency distribution. After analyzing the distribution of key, load balance of data partition is achieved. Results show that the Dynamic Re-Partitioning function is better than the default Hash partition, Fine Partition and the Balanced-Schedule strategy, it can reduce the execution time of the task and improve the efficiency of the whole cluster.

Fully Decomposable Split Graphs

NASA Astrophysics Data System (ADS)

Broersma, Hajo; Kratsch, Dieter; Woeginger, Gerhard J.

We discuss various questions around partitioning a split graph into connected parts. Our main result is a polynomial time algorithm that decides whether a given split graph is fully decomposable, i.e., whether it can be partitioned into connected parts of order α 1,α 2,...,α k for every α 1,α 2,...,α k summing up to the order of the graph. In contrast, we show that the decision problem whether a given split graph can be partitioned into connected parts of order α 1,α 2,...,α k for a given partition α 1,α 2,...,α k of the order of the graph, is NP-hard.

Task-specific image partitioning.

PubMed

Kim, Sungwoong; Nowozin, Sebastian; Kohli, Pushmeet; Yoo, Chang D

2013-02-01

Image partitioning is an important preprocessing step for many of the state-of-the-art algorithms used for performing high-level computer vision tasks. Typically, partitioning is conducted without regard to the task in hand. We propose a task-specific image partitioning framework to produce a region-based image representation that will lead to a higher task performance than that reached using any task-oblivious partitioning framework and existing supervised partitioning framework, albeit few in number. The proposed method partitions the image by means of correlation clustering, maximizing a linear discriminant function defined over a superpixel graph. The parameters of the discriminant function that define task-specific similarity/dissimilarity among superpixels are estimated based on structured support vector machine (S-SVM) using task-specific training data. The S-SVM learning leads to a better generalization ability while the construction of the superpixel graph used to define the discriminant function allows a rich set of features to be incorporated to improve discriminability and robustness. We evaluate the learned task-aware partitioning algorithms on three benchmark datasets. Results show that task-aware partitioning leads to better labeling performance than the partitioning computed by the state-of-the-art general-purpose and supervised partitioning algorithms. We believe that the task-specific image partitioning paradigm is widely applicable to improving performance in high-level image understanding tasks.

QSPR modeling of octanol/water partition coefficient of antineoplastic agents by balance of correlations.

PubMed

Toropov, Andrey A; Toropova, Alla P; Raska, Ivan; Benfenati, Emilio

2010-04-01

Three different splits into the subtraining set (n = 22), the set of calibration (n = 21), and the test set (n = 12) of 55 antineoplastic agents have been examined. By the correlation balance of SMILES-based optimal descriptors quite satisfactory models for the octanol/water partition coefficient have been obtained on all three splits. The correlation balance is the optimization of a one-variable model with a target function that provides both the maximal values of the correlation coefficient for the subtraining and calibration set and the minimum of the difference between the above-mentioned correlation coefficients. Thus, the calibration set is a preliminary test set. Copyright (c) 2009 Elsevier Masson SAS. All rights reserved.

Equivalence of partition properties and determinacy

PubMed Central

Kechris, Alexander S.; Woodin, W. Hugh

1983-01-01

It is shown that, within L(ℝ), the smallest inner model of set theory containing the reals, the axiom of determinacy is equivalent to the existence of arbitrarily large cardinals below Θ with the strong partition property κ → (κ)κ. PMID:16593299

Wavelet compression of multichannel ECG data by enhanced set partitioning in hierarchical trees algorithm.

PubMed

Sharifahmadian, Ershad

2006-01-01

The set partitioning in hierarchical trees (SPIHT) algorithm is very effective and computationally simple technique for image and signal compression. Here the author modified the algorithm which provides even better performance than the SPIHT algorithm. The enhanced set partitioning in hierarchical trees (ESPIHT) algorithm has performance faster than the SPIHT algorithm. In addition, the proposed algorithm reduces the number of bits in a bit stream which is stored or transmitted. I applied it to compression of multichannel ECG data. Also, I presented a specific procedure based on the modified algorithm for more efficient compression of multichannel ECG data. This method employed on selected records from the MIT-BIH arrhythmia database. According to experiments, the proposed method attained the significant results regarding compression of multichannel ECG data. Furthermore, in order to compress one signal which is stored for a long time, the proposed multichannel compression method can be utilized efficiently.

Robust MST-Based Clustering Algorithm.

PubMed

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

Eigenvector synchronization, graph rigidity and the molecule problemR

PubMed Central

Cucuringu, Mihai; Singer, Amit; Cowburn, David

2013-01-01

The graph realization problem has received a great deal of attention in recent years, due to its importance in applications such as wireless sensor networks and structural biology. In this paper, we extend the previous work and propose the 3D-As-Synchronized-As-Possible (3D-ASAP) algorithm, for the graph realization problem in ℝ3, given a sparse and noisy set of distance measurements. 3D-ASAP is a divide and conquer, non-incremental and non-iterative algorithm, which integrates local distance information into a global structure determination. Our approach starts with identifying, for every node, a subgraph of its 1-hop neighborhood graph, which can be accurately embedded in its own coordinate system. In the noise-free case, the computed coordinates of the sensors in each patch must agree with their global positioning up to some unknown rigid motion, that is, up to translation, rotation and possibly reflection. In other words, to every patch, there corresponds an element of the Euclidean group, Euc(3), of rigid transformations in ℝ3, and the goal was to estimate the group elements that will properly align all the patches in a globally consistent way. Furthermore, 3D-ASAP successfully incorporates information specific to the molecule problem in structural biology, in particular information on known substructures and their orientation. In addition, we also propose 3D-spectral-partitioning (SP)-ASAP, a faster version of 3D-ASAP, which uses a spectral partitioning algorithm as a pre-processing step for dividing the initial graph into smaller subgraphs. Our extensive numerical simulations show that 3D-ASAP and 3D-SP-ASAP are very robust to high levels of noise in the measured distances and to sparse connectivity in the measurement graph, and compare favorably with similar state-of-the-art localization algorithms. PMID:24432187

Additional support for Afrotheria and Paenungulata, the performance of mitochondrial versus nuclear genes, and the impact of data partitions with heterogeneous base composition.

PubMed

Springer, M S; Amrine, H M; Burk, A; Stanhope, M J

1999-03-01

We concatenated sequences for four mitochondrial genes (12S rRNA, tRNA valine, 16S rRNA, cytochrome b) and four nuclear genes [aquaporin, alpha 2B adrenergic receptor (A2AB), interphotoreceptor retinoid-binding protein (IRBP), von Willebrand factor (vWF)] into a multigene data set representing 11 eutherian orders (Artiodactyla, Hyracoidea, Insectivora, Lagomorpha, Macroscelidea, Perissodactyla, Primates, Proboscidea, Rodentia, Sirenia, Tubulidentata). Within this data set, we recognized nine mitochondrial partitions (both stems and loops, for each of 12S rRNA, tRNA valine, and 16S rRNA; and first, second, and third codon positions of cytochrome b) and 12 nuclear partitions (first, second, and third codon positions, respectively, of each of the four nuclear genes). Four of the 21 partitions (third positions of cytochrome b, A2AB, IRBP, and vWF) showed significant heterogeneity in base composition across taxa. Phylogenetic analyses (parsimony, minimum evolution, maximum likelihood) based on sequences for all 21 partitions provide 99-100% bootstrap support for Afrotheria and Paenungulata. With the elimination of the four partitions exhibiting heterogeneity in base composition, there is also high bootstrap support (89-100%) for cow + horse. Statistical tests reject Altungulata, Anagalida, and Ungulata. Data set heterogeneity between mitochondrial and nuclear genes is most evident when all partitions are included in the phylogenetic analyses. Mitochondrial-gene trees associate cow with horse, whereas nuclear-gene trees associate cow with hedgehog and these two with horse. However, after eliminating third positions of A2AB, IRBP, and vWF, nuclear data agree with mitochondrial data in supporting cow + horse. Nuclear genes provide stronger support for both Afrotheria and Paenungulata. Removal of third positions of cytochrome b results in improved performance for the mitochondrial genes in recovering these clades.

Efficient partitioning and assignment on programs for multiprocessor execution

NASA Technical Reports Server (NTRS)

Standley, Hilda M.

1993-01-01

The general problem studied is that of segmenting or partitioning programs for distribution across a multiprocessor system. Efficient partitioning and the assignment of program elements are of great importance since the time consumed in this overhead activity may easily dominate the computation, effectively eliminating any gains made by the use of the parallelism. In this study, the partitioning of sequentially structured programs (written in FORTRAN) is evaluated. Heuristics, developed for similar applications are examined. Finally, a model for queueing networks with finite queues is developed which may be used to analyze multiprocessor system architectures with a shared memory approach to the problem of partitioning. The properties of sequentially written programs form obstacles to large scale (at the procedure or subroutine level) parallelization. Data dependencies of even the minutest nature, reflecting the sequential development of the program, severely limit parallelism. The design of heuristic algorithms is tied to the experience gained in the parallel splitting. Parallelism obtained through the physical separation of data has seen some success, especially at the data element level. Data parallelism on a grander scale requires models that accurately reflect the effects of blocking caused by finite queues. A model for the approximation of the performance of finite queueing networks is developed. This model makes use of the decomposition approach combined with the efficiency of product form solutions.

An evaluation of exact methods for the multiple subset maximum cardinality selection problem.

PubMed

Brusco, Michael J; Köhn, Hans-Friedrich; Steinley, Douglas

2016-05-01

The maximum cardinality subset selection problem requires finding the largest possible subset from a set of objects, such that one or more conditions are satisfied. An important extension of this problem is to extract multiple subsets, where the addition of one more object to a larger subset would always be preferred to increases in the size of one or more smaller subsets. We refer to this as the multiple subset maximum cardinality selection problem (MSMCSP). A recently published branch-and-bound algorithm solves the MSMCSP as a partitioning problem. Unfortunately, the computational requirement associated with the algorithm is often enormous, thus rendering the method infeasible from a practical standpoint. In this paper, we present an alternative approach that successively solves a series of binary integer linear programs to obtain a globally optimal solution to the MSMCSP. Computational comparisons of the methods using published similarity data for 45 food items reveal that the proposed sequential method is computationally far more efficient than the branch-and-bound approach. © 2016 The British Psychological Society.

Methods for selecting fixed-effect models for heterogeneous codon evolution, with comments on their application to gene and genome data.

PubMed

Bao, Le; Gu, Hong; Dunn, Katherine A; Bielawski, Joseph P

2007-02-08

Models of codon evolution have proven useful for investigating the strength and direction of natural selection. In some cases, a priori biological knowledge has been used successfully to model heterogeneous evolutionary dynamics among codon sites. These are called fixed-effect models, and they require that all codon sites are assigned to one of several partitions which are permitted to have independent parameters for selection pressure, evolutionary rate, transition to transversion ratio or codon frequencies. For single gene analysis, partitions might be defined according to protein tertiary structure, and for multiple gene analysis partitions might be defined according to a gene's functional category. Given a set of related fixed-effect models, the task of selecting the model that best fits the data is not trivial. In this study, we implement a set of fixed-effect codon models which allow for different levels of heterogeneity among partitions in the substitution process. We describe strategies for selecting among these models by a backward elimination procedure, Akaike information criterion (AIC) or a corrected Akaike information criterion (AICc). We evaluate the performance of these model selection methods via a simulation study, and make several recommendations for real data analysis. Our simulation study indicates that the backward elimination procedure can provide a reliable method for model selection in this setting. We also demonstrate the utility of these models by application to a single-gene dataset partitioned according to tertiary structure (abalone sperm lysin), and a multi-gene dataset partitioned according to the functional category of the gene (flagellar-related proteins of Listeria). Fixed-effect models have advantages and disadvantages. Fixed-effect models are desirable when data partitions are known to exhibit significant heterogeneity or when a statistical test of such heterogeneity is desired. They have the disadvantage of requiring a priori knowledge for partitioning sites. We recommend: (i) selection of models by using backward elimination rather than AIC or AICc, (ii) use a stringent cut-off, e.g., p = 0.0001, and (iii) conduct sensitivity analysis of results. With thoughtful application, fixed-effect codon models should provide a useful tool for large scale multi-gene analyses.

SCOUT: simultaneous time segmentation and community detection in dynamic networks

PubMed Central

Hulovatyy, Yuriy; Milenković, Tijana

2016-01-01

Many evolving complex real-world systems can be modeled via dynamic networks. An important problem in dynamic network research is community detection, which finds groups of topologically related nodes. Typically, this problem is approached by assuming either that each time point has a distinct community organization or that all time points share a single community organization. The reality likely lies between these two extremes. To find the compromise, we consider community detection in the context of the problem of segment detection, which identifies contiguous time periods with consistent network structure. Consequently, we formulate a combined problem of segment community detection (SCD), which simultaneously partitions the network into contiguous time segments with consistent community organization and finds this community organization for each segment. To solve SCD, we introduce SCOUT, an optimization framework that explicitly considers both segmentation quality and partition quality. SCOUT addresses limitations of existing methods that can be adapted to solve SCD, which consider only one of segmentation quality or partition quality. In a thorough evaluation, SCOUT outperforms the existing methods in terms of both accuracy and computational complexity. We apply SCOUT to biological network data to study human aging. PMID:27881879

Connected Component Model for Multi-Object Tracking.

PubMed

He, Zhenyu; Li, Xin; You, Xinge; Tao, Dacheng; Tang, Yuan Yan

2016-08-01

In multi-object tracking, it is critical to explore the data associations by exploiting the temporal information from a sequence of frames rather than the information from the adjacent two frames. Since straightforwardly obtaining data associations from multi-frames is an NP-hard multi-dimensional assignment (MDA) problem, most existing methods solve this MDA problem by either developing complicated approximate algorithms, or simplifying MDA as a 2D assignment problem based upon the information extracted only from adjacent frames. In this paper, we show that the relation between associations of two observations is the equivalence relation in the data association problem, based on the spatial-temporal constraint that the trajectories of different objects must be disjoint. Therefore, the MDA problem can be equivalently divided into independent subproblems by equivalence partitioning. In contrast to existing works for solving the MDA problem, we develop a connected component model (CCM) by exploiting the constraints of the data association and the equivalence relation on the constraints. Based upon CCM, we can efficiently obtain the global solution of the MDA problem for multi-object tracking by optimizing a sequence of independent data association subproblems. Experiments on challenging public data sets demonstrate that our algorithm outperforms the state-of-the-art approaches.

Partitioning a macroscopic system into independent subsystems

NASA Astrophysics Data System (ADS)

Delle Site, Luigi; Ciccotti, Giovanni; Hartmann, Carsten

2017-08-01

We discuss the problem of partitioning a macroscopic system into a collection of independent subsystems. The partitioning of a system into replica-like subsystems is nowadays a subject of major interest in several fields of theoretical and applied physics. The thermodynamic approach currently favoured by practitioners is based on a phenomenological definition of an interface energy associated with the partition, due to a lack of easily computable expressions for a microscopic (i.e. particle-based) interface energy. In this article, we outline a general approach to derive sharp and computable bounds for the interface free energy in terms of microscopic statistical quantities. We discuss potential applications in nanothermodynamics and outline possible future directions.

Improved parallel data partitioning by nested dissection with applications to information retrieval.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wolf, Michael M.; Chevalier, Cedric; Boman, Erik Gunnar

The computational work in many information retrieval and analysis algorithms is based on sparse linear algebra. Sparse matrix-vector multiplication is a common kernel in many of these computations. Thus, an important related combinatorial problem in parallel computing is how to distribute the matrix and the vectors among processors so as to minimize the communication cost. We focus on minimizing the total communication volume while keeping the computation balanced across processes. In [1], the first two authors presented a new 2D partitioning method, the nested dissection partitioning algorithm. In this paper, we improve on that algorithm and show that it ismore » a good option for data partitioning in information retrieval. We also show partitioning time can be substantially reduced by using the SCOTCH software, and quality improves in some cases, too.« less

Cache Sharing and Isolation Tradeoffs in Multicore Mixed-Criticality Systems

DTIC Science & Technology

2015-05-01

of lockdown registers, to provide way-based partitioning. These alternatives are illustrated in Fig. 1 with respect to a quad-core ARM Cortex A9...presented a cache-partitioning scheme that allows multiple tasks to share the same cache partition on a single processor (as we do for Level-A and...sets and determined the fraction that were schedulable on our target hardware platform, the quad-core ARM Cortex A9 machine mentioned earlier, the LLC

Biogeochemical regions of the Mediterranean Sea: An objective multidimensional and multivariate environmental approach

NASA Astrophysics Data System (ADS)

Reygondeau, Gabriel; Guieu, Cécile; Benedetti, Fabio; Irisson, Jean-Olivier; Ayata, Sakina-Dorothée; Gasparini, Stéphane; Koubbi, Philippe

2017-02-01

When dividing the ocean, the aim is generally to summarise a complex system into a representative number of units, each representing a specific environment, a biological community or a socio-economical specificity. Recently, several geographical partitions of the global ocean have been proposed using statistical approaches applied to remote sensing or observations gathered during oceanographic cruises. Such geographical frameworks defined at a macroscale appear hardly applicable to characterise the biogeochemical features of semi-enclosed seas that are driven by smaller-scale chemical and physical processes. Following the Longhurst's biogeochemical partitioning of the pelagic realm, this study investigates the environmental divisions of the Mediterranean Sea using a large set of environmental parameters. These parameters were informed in the horizontal and the vertical dimensions to provide a 3D spatial framework for environmental management (12 regions found for the epipelagic, 12 for the mesopelagic, 13 for the bathypelagic and 26 for the seafloor). We show that: (1) the contribution of the longitudinal environmental gradient to the biogeochemical partitions decreases with depth; (2) the partition of the surface layer cannot be extrapolated to other vertical layers as the partition is driven by a different set of environmental variables. This new partitioning of the Mediterranean Sea has strong implications for conservation as it highlights that management must account for the differences in zoning with depth at a regional scale.

Topics

ERIC Educational Resources Information Center

Mathematics Teaching, 1972

1972-01-01

Topics discussed in this column include patterns of inverse multipliers in modular arithmetic; diagrams for product sets, set intersection, and set union; function notation; patterns in the number of partitions of positive integers; and tessellations. (DT)

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data.

PubMed

Veganzones, Miguel A; Simoes, Miguel; Licciardi, Giorgio; Yokoya, Naoto; Bioucas-Dias, Jose M; Chanussot, Jocelyn

2016-01-01

Remote sensing hyperspectral images (HSIs) are quite often low rank, in the sense that the data belong to a low dimensional subspace/manifold. This has been recently exploited for the fusion of low spatial resolution HSI with high spatial resolution multispectral images in order to obtain super-resolution HSI. Most approaches adopt an unmixing or a matrix factorization perspective. The derived methods have led to state-of-the-art results when the spectral information lies in a low-dimensional subspace/manifold. However, if the subspace/manifold dimensionality spanned by the complete data set is large, i.e., larger than the number of multispectral bands, the performance of these methods mainly decreases because the underlying sparse regression problem is severely ill-posed. In this paper, we propose a local approach to cope with this difficulty. Fundamentally, we exploit the fact that real world HSIs are locally low rank, that is, pixels acquired from a given spatial neighborhood span a very low-dimensional subspace/manifold, i.e., lower or equal than the number of multispectral bands. Thus, we propose to partition the image into patches and solve the data fusion problem independently for each patch. This way, in each patch the subspace/manifold dimensionality is low enough, such that the problem is not ill-posed anymore. We propose two alternative approaches to define the hyperspectral super-resolution through local dictionary learning using endmember induction algorithms. We also explore two alternatives to define the local regions, using sliding windows and binary partition trees. The effectiveness of the proposed approaches is illustrated with synthetic and semi real data.

Random Partition Distribution Indexed by Pairwise Information

PubMed Central

Dahl, David B.; Day, Ryan; Tsai, Jerry W.

2017-01-01

We propose a random partition distribution indexed by pairwise similarity information such that partitions compatible with the similarities are given more probability. The use of pairwise similarities, in the form of distances, is common in some clustering algorithms (e.g., hierarchical clustering), but we show how to use this type of information to define a prior partition distribution for flexible Bayesian modeling. A defining feature of the distribution is that it allocates probability among partitions within a given number of subsets, but it does not shift probability among sets of partitions with different numbers of subsets. Our distribution places more probability on partitions that group similar items yet keeps the total probability of partitions with a given number of subsets constant. The distribution of the number of subsets (and its moments) is available in closed-form and is not a function of the similarities. Our formulation has an explicit probability mass function (with a tractable normalizing constant) so the full suite of MCMC methods may be used for posterior inference. We compare our distribution with several existing partition distributions, showing that our formulation has attractive properties. We provide three demonstrations to highlight the features and relative performance of our distribution. PMID:29276318

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-07-17

The explosion of biological data has largely influenced the focus of today’s biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Integrated simultaneous analysis of different biomedical data types with exact weighted bi-cluster editing.

PubMed

Sun, Peng; Guo, Jiong; Baumbach, Jan

2012-06-01

The explosion of biological data has largely influenced the focus of today's biology research. Integrating and analysing large quantity of data to provide meaningful insights has become the main challenge to biologists and bioinformaticians. One major problem is the combined data analysis of data from different types, such as phenotypes and genotypes. This data is modelled as bi-partite graphs where nodes correspond to the different data points, mutations and diseases for instance, and weighted edges relate to associations between them. Bi-clustering is a special case of clustering designed for partitioning two different types of data simultaneously. We present a bi-clustering approach that solves the NP-hard weighted bi-cluster editing problem by transforming a given bi-partite graph into a disjoint union of bi-cliques. Here we contribute with an exact algorithm that is based on fixed-parameter tractability. We evaluated its performance on artificial graphs first. Afterwards we exemplarily applied our Java implementation to data of genome-wide association studies (GWAS) data aiming for discovering new, previously unobserved geno-to-pheno associations. We believe that our results will serve as guidelines for further wet lab investigations. Generally our software can be applied to any kind of data that can be modelled as bi-partite graphs. To our knowledge it is the fastest exact method for weighted bi-cluster editing problem.

Partitioning Algorithms for Simultaneously Balancing Iterative and Direct Methods

DTIC Science & Technology

2004-03-03

is defined as 57698&:&;=<$>?8A@B8 DC E & /F <G8H IJ0 K L 012 1NM? which is the ratio of the highest partition weight over the average...OQPSR , 57698T:;=<$>U8T@B8 DC E & /VXWZYK[\\O , and E :^] E_CU`4ab /V is minimized. The load imbalance is the constraint we have to satisfy, and...that the initial partitioning can be improved [16, 19, 20]. 3 Problem Definition and Challenges Consider a graph )c2 with d e f vertices

Life prediction of thermal-mechanical fatigue using strainrange partitioning

NASA Technical Reports Server (NTRS)

Halford, G. R.; Manson, S. S.

1975-01-01

This paper describes the applicability of the method of Strainrange Partitioning to the life prediction of thermal-mechanical strain-cycling fatigue. An in-phase test on 316 stainless steel is analyzed as an illustrative example. The observed life is in excellent agreement with the life predicted by the method using the recently proposed Step-Stress Method of experimental partitioning, the Interaction Damage Rule, and the life relationships determined at an isothermal temperature of 705 C. Implications of the present study are discussed relative to the general thermal fatigue problem.

Life prediction of thermal-mechanical fatigue using strain-range partitioning

NASA Technical Reports Server (NTRS)

Halford, G. R.; Manson, S. S.

1975-01-01

The applicability is described of the method of Strainrange Partitioning to the life prediction of thermal-mechanical strain-cycling fatigue. An in-phase test on 316 stainless steel is analyzed as an illustrative example. The observed life is in excellent agreement with the life predicted by the method using the recently proposed Step-Stress Method of experimental partitioning, the Interation Damage Rule, and the life relationships determined at an isothermal temperature of 705 C. Implications of the study are discussed relative to the general thermal fatigue problem.

Variance-Based Cluster Selection Criteria in a K-Means Framework for One-Mode Dissimilarity Data.

PubMed

Vera, J Fernando; Macías, Rodrigo

2017-06-01

One of the main problems in cluster analysis is that of determining the number of groups in the data. In general, the approach taken depends on the cluster method used. For K-means, some of the most widely employed criteria are formulated in terms of the decomposition of the total point scatter, regarding a two-mode data set of N points in p dimensions, which are optimally arranged into K classes. This paper addresses the formulation of criteria to determine the number of clusters, in the general situation in which the available information for clustering is a one-mode [Formula: see text] dissimilarity matrix describing the objects. In this framework, p and the coordinates of points are usually unknown, and the application of criteria originally formulated for two-mode data sets is dependent on their possible reformulation in the one-mode situation. The decomposition of the variability of the clustered objects is proposed in terms of the corresponding block-shaped partition of the dissimilarity matrix. Within-block and between-block dispersion values for the partitioned dissimilarity matrix are derived, and variance-based criteria are subsequently formulated in order to determine the number of groups in the data. A Monte Carlo experiment was carried out to study the performance of the proposed criteria. For simulated clustered points in p dimensions, greater efficiency in recovering the number of clusters is obtained when the criteria are calculated from the related Euclidean distances instead of the known two-mode data set, in general, for unequal-sized clusters and for low dimensionality situations. For simulated dissimilarity data sets, the proposed criteria always outperform the results obtained when these criteria are calculated from their original formulation, using dissimilarities instead of distances.

Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV).

PubMed

Piette, Elizabeth R; Moore, Jason H

2018-01-01

Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning analyses of GWAS can be hampered by biological and statistical factors, particularly so for the investigation of non-additive genetic interactions. Application of traditional cross validation to a GWAS data set may result in poor consistency between the training and testing data set splits due to an imbalance of the interaction genotypes relative to the data as a whole. We propose a new cross validation method, proportional instance cross validation (PICV), that preserves the original distribution of an independent variable when splitting the data set into training and testing partitions. We apply PICV to simulated GWAS data with epistatic interactions of varying minor allele frequencies and prevalences and compare performance to that of a traditional cross validation procedure in which individuals are randomly allocated to training and testing partitions. Sensitivity and positive predictive value are significantly improved across all tested scenarios for PICV compared to traditional cross validation. We also apply PICV to GWAS data from a study of primary open-angle glaucoma to investigate a previously-reported interaction, which fails to significantly replicate; PICV however improves the consistency of testing and training results. Application of traditional machine learning procedures to biomedical data may require modifications to better suit intrinsic characteristics of the data, such as the potential for highly imbalanced genotype distributions in the case of epistasis detection. The reproducibility of genetic interaction findings can be improved by considering this variable imbalance in cross validation implementation, such as with PICV. This approach may be extended to problems in other domains in which imbalanced variable distributions are a concern.

Benefits Assessment of the Interaction Between Traffic Flow Management Delay and Airspace Partitions in the Presence of Weather

NASA Technical Reports Server (NTRS)

Palopo, Kee; Lee, Hak-Tae; Chatterji, Gano

2011-01-01

The concept of re-partitioning the airspace into a new set of sectors for allocating capacity rather than delaying flights to comply with the capacity constraints of a static set of sectors is being explored. The reduction in delay, a benefit, achieved by this concept needs to be greater than the cost of controllers and equipment needed for the additional sectors. Therefore, tradeoff studies are needed for benefits assessment of this concept.

Architecture Aware Partitioning Algorithms

DTIC Science & Technology

2006-01-19

follows: Given a graph G = (V, E ), where V is the set of vertices, n = |V | is the number of vertices, and E is the set of edges in the graph, partition the...communication link l(pi, pj) is associated with a graph edge weight e ∗(pi, pj) that represents the communication cost per unit of communication between...one that is local for each one. For our model we assume that communication in either direction across a given link is the same, therefore e ∗(pi, pj

Specular reflection treatment for the 3D radiative transfer equation solved with the discrete ordinates method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Le Hardy, D.; Favennec, Y., E-mail: yann.favennec@univ-nantes.fr; Rousseau, B.

The contribution of this paper relies in the development of numerical algorithms for the mathematical treatment of specular reflection on borders when dealing with the numerical solution of radiative transfer problems. The radiative transfer equation being integro-differential, the discrete ordinates method allows to write down a set of semi-discrete equations in which weights are to be calculated. The calculation of these weights is well known to be based on either a quadrature or on angular discretization, making the use of such method straightforward for the state equation. Also, the diffuse contribution of reflection on borders is usually well taken intomore » account. However, the calculation of accurate partition ratio coefficients is much more tricky for the specular condition applied on arbitrary geometrical borders. This paper presents algorithms that calculate analytically partition ratio coefficients needed in numerical treatments. The developed algorithms, combined with a decentered finite element scheme, are validated with the help of comparisons with analytical solutions before being applied on complex geometries.« less

Knowledge-based modularization and global optimization of artificial neural network models in hydrological forecasting.

PubMed

Corzo, Gerald; Solomatine, Dimitri

2007-05-01

Natural phenomena are multistationary and are composed of a number of interacting processes, so one single model handling all processes often suffers from inaccuracies. A solution is to partition data in relation to such processes using the available domain knowledge or expert judgment, to train separate models for each of the processes, and to merge them in a modular model (committee). In this paper a problem of water flow forecast in watershed hydrology is considered where the flow process can be presented as consisting of two subprocesses -- base flow and excess flow, so that these two processes can be separated. Several approaches to data separation techniques are studied. Two case studies with different forecast horizons are considered. Parameters of the algorithms responsible for data partitioning are optimized using genetic algorithms and global pattern search. It was found that modularization of ANN models using domain knowledge makes models more accurate, if compared with a global model trained on the whole data set, especially when forecast horizon (and hence the complexity of the modelled processes) is increased.

On a modification method of Lefschetz thimbles

NASA Astrophysics Data System (ADS)

Tsutsui, Shoichiro; Doi, Takahiro M.

2018-03-01

The QCD at finite density is not well understood yet, where standard Monte Carlo simulation suffers from the sign problem. In order to overcome the sign problem, the method of Lefschetz thimble has been explored. Basically, the original sign problem can be less severe in a complexified theory due to the constancy of the imaginary part of an action on each thimble. However, global phase factors assigned on each thimble still remain. Their interference is not negligible in a situation where a large number of thimbles contribute to the partition function, and this could also lead to a sign problem. In this study, we propose a method to resolve this problem by modifying the structure of Lefschetz thimbles such that only a single thimble is relevant to the partition function. It can be shown that observables measured in the original and modified theories are connected by a simple identity. We exemplify that our method works well in a toy model.

Crashworthiness simulations with DYNA3D

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schauer, D.A.; Hoover, C.G.; Kay, G.J.

1996-04-01

Current progress in parallel algorithm research and applications in vehicle crash simulation is described for the explicit, finite element algorithms in DYNA3D. Problem partitioning methods and parallel algorithms for contact at material interfaces are the two challenging algorithm research problems that are addressed. Two prototype parallel contact algorithms have been developed for treating the cases of local and arbitrary contact. Demonstration problems for local contact are crashworthiness simulations with 222 locally defined contact surfaces and a vehicle/barrier collision modeled with arbitrary contact. A simulation of crash tests conducted for a vehicle impacting a U-channel small sign post embedded in soilmore » has been run on both the serial and parallel versions of DYNA3D. A significant reduction in computational time has been observed when running these problems on the parallel version. However, to achieve maximum efficiency, complex problems must be appropriately partitioned, especially when contact dominates the computation.« less

A Partitioning and Bounded Variable Algorithm for Linear Programming

ERIC Educational Resources Information Center

Sheskin, Theodore J.

2006-01-01

An interesting new partitioning and bounded variable algorithm (PBVA) is proposed for solving linear programming problems. The PBVA is a variant of the simplex algorithm which uses a modified form of the simplex method followed by the dual simplex method for bounded variables. In contrast to the two-phase method and the big M method, the PBVA does…

On the Partitioning of Squared Euclidean Distance and Its Applications in Cluster Analysis.

ERIC Educational Resources Information Center

Carter, Randy L.; And Others

1989-01-01

The partitioning of squared Euclidean--E(sup 2)--distance between two vectors in M-dimensional space into the sum of squared lengths of vectors in mutually orthogonal subspaces is discussed. Applications to specific cluster analysis problems are provided (i.e., to design Monte Carlo studies for performance comparisons of several clustering methods…

Using partially labeled data for normal mixture identification with application to class definition

NASA Technical Reports Server (NTRS)

Shahshahani, Behzad M.; Landgrebe, David A.

1992-01-01

The problem of estimating the parameters of a normal mixture density when, in addition to the unlabeled samples, sets of partially labeled samples are available is addressed. The density of the multidimensional feature space is modeled with a normal mixture. It is assumed that the set of components of the mixture can be partitioned into several classes and that training samples are available from each class. Since for any training sample the class of origin is known but the exact component of origin within the corresponding class is unknown, the training samples as considered to be partially labeled. The EM iterative equations are derived for estimating the parameters of the normal mixture in the presence of partially labeled samples. These equations can be used to combine the supervised and nonsupervised learning processes.

Estimation of octanol/water partition coefficients using LSER parameters

USGS Publications Warehouse

Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

1998-01-01

The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

Kinetic energy partition method applied to ground state helium-like atoms.

PubMed

Chen, Yu-Hsin; Chao, Sheng D

2017-03-28

We have used the recently developed kinetic energy partition (KEP) method to solve the quantum eigenvalue problems for helium-like atoms and obtain precise ground state energies and wave-functions. The key to treating properly the electron-electron (repulsive) Coulomb potential energies for the KEP method to be applied is to introduce a "negative mass" term into the partitioned kinetic energy. A Hartree-like product wave-function from the subsystem wave-functions is used to form the initial trial function, and the variational search for the optimized adiabatic parameters leads to a precise ground state energy. This new approach sheds new light on the all-important problem of solving many-electron Schrödinger equations and hopefully opens a new way to predictive quantum chemistry. The results presented here give very promising evidence that an effective one-electron model can be used to represent a many-electron system, in the spirit of density functional theory.

Development of parallel algorithms for electrical power management in space applications

NASA Technical Reports Server (NTRS)

Berry, Frederick C.

1989-01-01

The application of parallel techniques for electrical power system analysis is discussed. The Newton-Raphson method of load flow analysis was used along with the decomposition-coordination technique to perform load flow analysis. The decomposition-coordination technique enables tasks to be performed in parallel by partitioning the electrical power system into independent local problems. Each independent local problem represents a portion of the total electrical power system on which a loan flow analysis can be performed. The load flow analysis is performed on these partitioned elements by using the Newton-Raphson load flow method. These independent local problems will produce results for voltage and power which can then be passed to the coordinator portion of the solution procedure. The coordinator problem uses the results of the local problems to determine if any correction is needed on the local problems. The coordinator problem is also solved by an iterative method much like the local problem. The iterative method for the coordination problem will also be the Newton-Raphson method. Therefore, each iteration at the coordination level will result in new values for the local problems. The local problems will have to be solved again along with the coordinator problem until some convergence conditions are met.

PAQ: Partition Analysis of Quasispecies.

PubMed

Baccam, P; Thompson, R J; Fedrigo, O; Carpenter, S; Cornette, J L

2001-01-01

The complexities of genetic data may not be accurately described by any single analytical tool. Phylogenetic analysis is often used to study the genetic relationship among different sequences. Evolutionary models and assumptions are invoked to reconstruct trees that describe the phylogenetic relationship among sequences. Genetic databases are rapidly accumulating large amounts of sequences. Newly acquired sequences, which have not yet been characterized, may require preliminary genetic exploration in order to build models describing the evolutionary relationship among sequences. There are clustering techniques that rely less on models of evolution, and thus may provide nice exploratory tools for identifying genetic similarities. Some of the more commonly used clustering methods perform better when data can be grouped into mutually exclusive groups. Genetic data from viral quasispecies, which consist of closely related variants that differ by small changes, however, may best be partitioned by overlapping groups. We have developed an intuitive exploratory program, Partition Analysis of Quasispecies (PAQ), which utilizes a non-hierarchical technique to partition sequences that are genetically similar. PAQ was used to analyze a data set of human immunodeficiency virus type 1 (HIV-1) envelope sequences isolated from different regions of the brain and another data set consisting of the equine infectious anemia virus (EIAV) regulatory gene rev. Analysis of the HIV-1 data set by PAQ was consistent with phylogenetic analysis of the same data, and the EIAV rev variants were partitioned into two overlapping groups. PAQ provides an additional tool which can be used to glean information from genetic data and can be used in conjunction with other tools to study genetic similarities and genetic evolution of viral quasispecies.

Modeling of adipose/blood partition coefficient for environmental chemicals.

PubMed

Papadaki, K C; Karakitsios, S P; Sarigiannis, D A

2017-12-01

A Quantitative Structure Activity Relationship (QSAR) model was developed in order to predict the adipose/blood partition coefficient of environmental chemical compounds. The first step of QSAR modeling was the collection of inputs. Input data included the experimental values of adipose/blood partition coefficient and two sets of molecular descriptors for 67 organic chemical compounds; a) the descriptors from Linear Free Energy Relationship (LFER) and b) the PaDEL descriptors. The datasets were split to training and prediction set and were analysed using two statistical methods; Genetic Algorithm based Multiple Linear Regression (GA-MLR) and Artificial Neural Networks (ANN). The models with LFER and PaDEL descriptors, coupled with ANN, produced satisfying performance results. The fitting performance (R 2 ) of the models, using LFER and PaDEL descriptors, was 0.94 and 0.96, respectively. The Applicability Domain (AD) of the models was assessed and then the models were applied to a large number of chemical compounds with unknown values of adipose/blood partition coefficient. In conclusion, the proposed models were checked for fitting, validity and applicability. It was demonstrated that they are stable, reliable and capable to predict the values of adipose/blood partition coefficient of "data poor" chemical compounds that fall within the applicability domain. Copyright © 2017. Published by Elsevier Ltd.

Mass budget partitioning during explosive eruptions: insights from the 2006 paroxysm of Tungurahua volcano, Ecuador

NASA Astrophysics Data System (ADS)

Bernard, Julien; Eychenne, Julia; Le Pennec, Jean-Luc; Narváez, Diego

2016-08-01

How and how much the mass of juvenile magma is split between vent-derived tephra, PDC deposits and lavas (i.e., mass partition) is related to eruption dynamics and style. Estimating such mass partitioning budgets may reveal important for hazard evaluation purposes. We calculated the volume of each product emplaced during the August 2006 paroxysmal eruption of Tungurahua volcano (Ecuador) and converted it into masses using high-resolution grainsize, componentry and density data. This data set is one of the first complete descriptions of mass partitioning associated with a VEI 3 andesitic event. The scoria fall deposit, near-vent agglutinate and lava flow include 28, 16 and 12 wt. % of the erupted juvenile mass, respectively. Much (44 wt. %) of the juvenile material fed Pyroclastic Density Currents (i.e., dense flows, dilute surges and co-PDC plumes), highlighting that tephra fall deposits do not depict adequately the size and fragmentation processes of moderate PDC-forming event. The main parameters controlling the mass partitioning are the type of magmatic fragmentation, conditions of magma ascent, and crater area topography. Comparisons of our data set with other PDC-forming eruptions of different style and magma composition suggest that moderate andesitic eruptions are more prone to produce PDCs, in proportions, than any other eruption type. This finding may be explained by the relatively low magmatic fragmentation efficiency of moderate andesitic eruptions. These mass partitioning data reveal important trends that may be critical for hazard assessment, notably at frequently active andesitic edifices.

Dynamically heterogenous partitions and phylogenetic inference: an evaluation of analytical strategies with cytochrome b and ND6 gene sequences in cranes.

PubMed

Krajewski, C; Fain, M G; Buckley, L; King, D G

1999-11-01

ki ctes over whether molecular sequence data should be partitioned for phylogenetic analysis often confound two types of heterogeneity among partitions. We distinguish historical heterogeneity (i.e., different partitions have different evolutionary relationships) from dynamic heterogeneity (i.e., different partitions show different patterns of sequence evolution) and explore the impact of the latter on phylogenetic accuracy and precision with a two-gene, mitochondrial data set for cranes. The well-established phylogeny of cranes allows us to contrast tree-based estimates of relevant parameter values with estimates based on pairwise comparisons and to ascertain the effects of incorporating different amounts of process information into phylogenetic estimates. We show that codon positions in the cytochrome b and NADH dehydrogenase subunit 6 genes are dynamically heterogenous under both Poisson and invariable-sites + gamma-rates versions of the F84 model and that heterogeneity includes variation in base composition and transition bias as well as substitution rate. Estimates of transition-bias and relative-rate parameters from pairwise sequence comparisons were comparable to those obtained as tree-based maximum likelihood estimates. Neither rate-category nor mixed-model partitioning strategies resulted in a loss of phylogenetic precision relative to unpartitioned analyses. We suggest that weighted-average distances provide a computationally feasible alternative to direct maximum likelihood estimates of phylogeny for mixed-model analyses of large, dynamically heterogenous data sets. Copyright 1999 Academic Press.

Unsupervised hierarchical partitioning of hyperspectral images: application to marine algae identification

NASA Astrophysics Data System (ADS)

Chen, B.; Chehdi, K.; De Oliveria, E.; Cariou, C.; Charbonnier, B.

2015-10-01

In this paper a new unsupervised top-down hierarchical classification method to partition airborne hyperspectral images is proposed. The unsupervised approach is preferred because the difficulty of area access and the human and financial resources required to obtain ground truth data, constitute serious handicaps especially over large areas which can be covered by airborne or satellite images. The developed classification approach allows i) a successive partitioning of data into several levels or partitions in which the main classes are first identified, ii) an estimation of the number of classes automatically at each level without any end user help, iii) a nonsystematic subdivision of all classes of a partition Pj to form a partition Pj+1, iv) a stable partitioning result of the same data set from one run of the method to another. The proposed approach was validated on synthetic and real hyperspectral images related to the identification of several marine algae species. In addition to highly accurate and consistent results (correct classification rate over 99%), this approach is completely unsupervised. It estimates at each level, the optimal number of classes and the final partition without any end user intervention.

The prediction of blood-tissue partitions, water-skin partitions and skin permeation for agrochemicals.

PubMed

Abraham, Michael H; Gola, Joelle M R; Ibrahim, Adam; Acree, William E; Liu, Xiangli

2014-07-01

There is considerable interest in the blood-tissue distribution of agrochemicals, and a number of researchers have developed experimental methods for in vitro distribution. These methods involve the determination of saline-blood and saline-tissue partitions; not only are they indirect, but they do not yield the required in vivo distribution. The authors set out equations for gas-tissue and blood-tissue distribution, for partition from water into skin and for permeation from water through human skin. Together with Abraham descriptors for the agrochemicals, these equations can be used to predict values for all of these processes. The present predictions compare favourably with experimental in vivo blood-tissue distribution where available. The predictions require no more than simple arithmetic. The present method represents a much easier and much more economic way of estimating blood-tissue partitions than the method that uses saline-blood and saline-tissue partitions. It has the added advantages of yielding the required in vivo partitions and being easily extended to the prediction of partition of agrochemicals from water into skin and permeation from water through skin. © 2013 Society of Chemical Industry.

3d expansions of 5d instanton partition functions

NASA Astrophysics Data System (ADS)

Nieri, Fabrizio; Pan, Yiwen; Zabzine, Maxim

2018-04-01

We propose a set of novel expansions of Nekrasov's instanton partition functions. Focusing on 5d supersymmetric pure Yang-Mills theory with unitary gauge group on C_{q,{t}^{-1}}^2× S^1 , we show that the instanton partition function admits expansions in terms of partition functions of unitary gauge theories living on the 3d subspaces C_q× S^1 , C_{t^{-1}}× S^1 and their intersection along S^1 . These new expansions are natural from the BPS/CFT viewpoint, as they can be matched with W q,t correlators involving an arbitrary number of screening charges of two kinds. Our constructions generalize and interpolate existing results in the literature.

Intuitionistic uncertain linguistic partitioned Bonferroni means and their application to multiple attribute decision-making

NASA Astrophysics Data System (ADS)

Liu, Zhengmin; Liu, Peide

2017-04-01

The Bonferroni mean (BM) was originally introduced by Bonferroni and generalised by many other researchers due to its capacity to capture the interrelationship between input arguments. Nevertheless, in many situations, interrelationships do not always exist between all of the attributes. Attributes can be partitioned into several different categories and members of intra-partition are interrelated while no interrelationship exists between attributes of different partitions. In this paper, as complements to the existing generalisations of BM, we investigate the partitioned Bonferroni mean (PBM) under intuitionistic uncertain linguistic environments and develop two linguistic aggregation operators: intuitionistic uncertain linguistic partitioned Bonferroni mean (IULPBM) and its weighted form (WIULPBM). Then, motivated by the ideal of geometric mean and PBM, we further present the partitioned geometric Bonferroni mean (PGBM) and develop two linguistic geometric aggregation operators: intuitionistic uncertain linguistic partitioned geometric Bonferroni mean (IULPGBM) and its weighted form (WIULPGBM). Some properties and special cases of these proposed operators are also investigated and discussed in detail. Based on these operators, an approach for multiple attribute decision-making problems with intuitionistic uncertain linguistic information is developed. Finally, a practical example is presented to illustrate the developed approach and comparison analyses are conducted with other representative methods to verify the effectiveness and feasibility of the developed approach.

47 CFR 80.60 - Partitioned licenses and disaggregated spectrum.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 5 2013-10-01 2013-10-01 false Partitioned licenses and disaggregated spectrum... licenses and disaggregated spectrum. (a) Except as specified in § 20.15(c) of this chapter with respect to... spectrum pursuant to the procedures set forth in this section. (2) AMTS geographic area licensees, see § 80...

47 CFR 80.60 - Partitioned licenses and disaggregated spectrum.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 5 2010-10-01 2010-10-01 false Partitioned licenses and disaggregated spectrum... licenses and disaggregated spectrum. (a) Except as specified in § 20.15(c) of this chapter with respect to... spectrum pursuant to the procedures set forth in this section. (2) AMTS geographic area licensees, see § 80...

47 CFR 80.60 - Partitioned licenses and disaggregated spectrum.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 5 2014-10-01 2014-10-01 false Partitioned licenses and disaggregated spectrum... licenses and disaggregated spectrum. (a) Except as specified in § 20.15(c) of this chapter with respect to... spectrum pursuant to the procedures set forth in this section. (2) AMTS geographic area licensees, see § 80...

47 CFR 80.60 - Partitioned licenses and disaggregated spectrum.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 5 2012-10-01 2012-10-01 false Partitioned licenses and disaggregated spectrum... licenses and disaggregated spectrum. (a) Except as specified in § 20.15(c) of this chapter with respect to... spectrum pursuant to the procedures set forth in this section. (2) AMTS geographic area licensees, see § 80...

47 CFR 80.60 - Partitioned licenses and disaggregated spectrum.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 5 2011-10-01 2011-10-01 false Partitioned licenses and disaggregated spectrum... licenses and disaggregated spectrum. (a) Except as specified in § 20.15(c) of this chapter with respect to... spectrum pursuant to the procedures set forth in this section. (2) AMTS geographic area licensees, see § 80...

A Novel Method for Discovering Fuzzy Sequential Patterns Using the Simple Fuzzy Partition Method.

ERIC Educational Resources Information Center

Chen, Ruey-Shun; Hu, Yi-Chung

2003-01-01

Discusses sequential patterns, data mining, knowledge acquisition, and fuzzy sequential patterns described by natural language. Proposes a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method which allows the linguistic interpretation of each fuzzy set to be easily obtained. (Author/LRW)

Finding and testing network communities by lumped Markov chains.

PubMed

Piccardi, Carlo

2011-01-01

Identifying communities (or clusters), namely groups of nodes with comparatively strong internal connectivity, is a fundamental task for deeply understanding the structure and function of a network. Yet, there is a lack of formal criteria for defining communities and for testing their significance. We propose a sharp definition that is based on a quality threshold. By means of a lumped Markov chain model of a random walker, a quality measure called "persistence probability" is associated to a cluster, which is then defined as an "α-community" if such a probability is not smaller than α. Consistently, a partition composed of α-communities is an "α-partition." These definitions turn out to be very effective for finding and testing communities. If a set of candidate partitions is available, setting the desired α-level allows one to immediately select the α-partition with the finest decomposition. Simultaneously, the persistence probabilities quantify the quality of each single community. Given its ability in individually assessing each single cluster, this approach can also disclose single well-defined communities even in networks that overall do not possess a definite clusterized structure.

Comment on “Rethinking first-principles electron transport theories with projection operators: The problems caused by partitioning the basis set” [J. Chem. Phys. 139, 114104 (2013)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brandbyge, Mads, E-mail: mads.brandbyge@nanotech.dtu.dk

2014-05-07

In a recent paper Reuter and Harrison [J. Chem. Phys. 139, 114104 (2013)] question the widely used mean-field electron transport theories, which employ nonorthogonal localized basis sets. They claim these can violate an “implicit decoupling assumption,” leading to wrong results for the current, different from what would be obtained by using an orthogonal basis, and dividing surfaces defined in real-space. We argue that this assumption is not required to be fulfilled to get exact results. We show how the current/transmission calculated by the standard Greens function method is independent of whether or not the chosen basis set is nonorthogonal, andmore » that the current for a given basis set is consistent with divisions in real space. The ambiguity known from charge population analysis for nonorthogonal bases does not carry over to calculations of charge flux.« less

A Dynamic Laplacian for Identifying Lagrangian Coherent Structures on Weighted Riemannian Manifolds

NASA Astrophysics Data System (ADS)

Froyland, Gary; Kwok, Eric

2017-06-01

Transport and mixing in dynamical systems are important properties for many physical, chemical, biological, and engineering processes. The detection of transport barriers for dynamics with general time dependence is a difficult, but important problem, because such barriers control how rapidly different parts of phase space (which might correspond to different chemical or biological agents) interact. The key factor is the growth of interfaces that partition phase space into separate regions. The paper Froyland (Nonlinearity 28(10):3587-3622, 2015) introduced the notion of dynamic isoperimetry: the study of sets with persistently small boundary size (the interface) relative to enclosed volume, when evolved by the dynamics. Sets with this minimal boundary size to volume ratio were identified as level sets of dominant eigenfunctions of a dynamic Laplace operator. In this present work we extend the results of Froyland (Nonlinearity 28(10):3587-3622, 2015) to the situation where the dynamics (1) is not necessarily volume preserving, (2) acts on initial agent concentrations different from uniform concentrations, and (3) occurs on a possibly curved phase space. Our main results include generalised versions of the dynamic isoperimetric problem, the dynamic Laplacian, Cheeger's inequality, and the Federer-Fleming theorem. We illustrate the computational approach with some simple numerical examples.

Design of a Recommendation System for Adding Support in the Treatment of Chronic Patients.

PubMed

Torkar, Simon; Benedik, Peter; Rajkovič, Uroš; Šušteršič, Olga; Rajkovič, Vladislav

2016-01-01

Rapid growth of chronic disease cases around the world is adding pressure on healthcare providers to ensure a structured patent follow-up during chronic disease management process. In response to the increasing demand for better chronic disease management and improved health care efficiency, nursing roles have been specialized or enhanced in the primary health care setting. Nurses become key players in chronic disease management process. Study describes a system to help nurses manage the care process of patient with chronic disease. It supports focusing nurse's attention on those resources/solutions that are likely to be most relevant to their particular situation/problem in nursing domain. System is based on multi-relational property graph representing a flexible modeling construct. Graph allows modeling a nursing ontology and the indices that partition domain into an efficient, searchable space where the solution to a problem is seen as abstractly defined traversals through its vertices and edges.

Dynamic connectivity regression: Determining state-related changes in brain connectivity

PubMed Central

Cribben, Ivor; Haraldsdottir, Ragnheidur; Atlas, Lauren Y.; Wager, Tor D.; Lindquist, Martin A.

2014-01-01

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method’s ability to observe how the networks between different brain regions changed with subjects’ emotional state. PMID:22484408

Combined spectroscopic imaging and chemometric approach for automatically partitioning tissue types in human prostate tissue biopsies

NASA Astrophysics Data System (ADS)

Haka, Abigail S.; Kidder, Linda H.; Lewis, E. Neil

2001-07-01

We have applied Fourier transform infrared (FTIR) spectroscopic imaging, coupling a mercury cadmium telluride (MCT) focal plane array detector (FPA) and a Michelson step scan interferometer, to the investigation of various states of malignant human prostate tissue. The MCT FPA used consists of 64x64 pixels, each 61 micrometers 2, and has a spectral range of 2-10.5 microns. Each imaging data set was collected at 16-1 resolution, resulting in 512 image planes and a total of 4096 interferograms. In this article we describe a method for separating different tissue types contained within FTIR spectroscopic imaging data sets of human prostate tissue biopsies. We present images, generated by the Fuzzy C-Means clustering algorithm, which demonstrate the successful partitioning of distinct tissue type domains. Additionally, analysis of differences in the centroid spectra corresponding to different tissue types provides an insight into their biochemical composition. Lastly, we demonstrate the ability to partition tissue type regions in a different data set using centroid spectra calculated from the original data set. This has implications for the use of the Fuzzy C-Means algorithm as an automated technique for the separation and examination of tissue domains in biopsy samples.

Sensitivity of Aerosol Mass and Microphysics to Treatments of Condensational Growth of Secondary Organic Compounds in a Regional Model

NASA Astrophysics Data System (ADS)

Topping, D. O.; Lowe, D.; McFiggans, G.; Zaveri, R. A.

2016-12-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight.For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin volatility basis set (VBS) treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organic compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased.This work was supported by the Nature Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

Surveillance system and method having parameter estimation and operating mode partitioning

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor)

2005-01-01

A system and method for monitoring an apparatus or process asset including creating a process model comprised of a plurality of process submodels each correlative to at least one training data subset partitioned from an unpartitioned training data set and each having an operating mode associated thereto; acquiring a set of observed signal data values from the asset; determining an operating mode of the asset for the set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a set of estimated signal data values from the selected process submodel for the determined operating mode; and determining asset status as a function of the calculated set of estimated signal data values for providing asset surveillance and/or control.

Data-Driven Online and Real-Time Combinatorial Optimization

DTIC Science & Technology

2013-10-30

Problem , the online Traveling Salesman Problem , and variations of the online Quota Hamil- tonian Path Problem and the online Traveling ...has the lowest competitive ratio among all algorithms of this kind. Second, we consider the Online Traveling Salesman Problem , and consider randomized...matroid secretary problem on a partition matroid. 6. Jaillet, P. and X. Lu. “Online Traveling Salesman Problems with Rejection Options”, submitted

Generalization of multifractal theory within quantum calculus

NASA Astrophysics Data System (ADS)

Olemskoi, A.; Shuda, I.; Borisyuk, V.

2010-03-01

On the basis of the deformed series in quantum calculus, we generalize the partition function and the mass exponent of a multifractal, as well as the average of a random variable distributed over a self-similar set. For the partition function, such expansion is shown to be determined by binomial-type combinations of the Tsallis entropies related to manifold deformations, while the mass exponent expansion generalizes the known relation τq=Dq(q-1). We find the equation for the set of averages related to ordinary, escort, and generalized probabilities in terms of the deformed expansion as well. Multifractals related to the Cantor binomial set, exchange currency series, and porous-surface condensates are considered as examples.

Detection of Problem Gambler Subgroups Using Recursive Partitioning

ERIC Educational Resources Information Center

Markham, Francis; Young, Martin; Doran, Bruce

2013-01-01

The multivariate socio-demographic risk factors for problem gambling have been well documented. While this body of research is valuable in determining risk factors aggregated across various populations, the majority of studies tend not to specifically identify particular subgroups of problem gamblers based on the interaction between variables. The…

Automatic data partitioning on distributed memory multicomputers. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Gupta, Manish

1992-01-01

Distributed-memory parallel computers are increasingly being used to provide high levels of performance for scientific applications. Unfortunately, such machines are not very easy to program. A number of research efforts seek to alleviate this problem by developing compilers that take over the task of generating communication. The communication overheads and the extent of parallelism exploited in the resulting target program are determined largely by the manner in which data is partitioned across different processors of the machine. Most of the compilers provide no assistance to the programmer in the crucial task of determining a good data partitioning scheme. A novel approach is presented, the constraints-based approach, to the problem of automatic data partitioning for numeric programs. In this approach, the compiler identifies some desirable requirements on the distribution of various arrays being referenced in each statement, based on performance considerations. These desirable requirements are referred to as constraints. For each constraint, the compiler determines a quality measure that captures its importance with respect to the performance of the program. The quality measure is obtained through static performance estimation, without actually generating the target data-parallel program with explicit communication. Each data distribution decision is taken by combining all the relevant constraints. The compiler attempts to resolve any conflicts between constraints such that the overall execution time of the parallel program is minimized. This approach has been implemented as part of a compiler called Paradigm, that accepts Fortran 77 programs, and specifies the partitioning scheme to be used for each array in the program. We have obtained results on some programs taken from the Linpack and Eispack libraries, and the Perfect Benchmarks. These results are quite promising, and demonstrate the feasibility of automatic data partitioning for a significant class of scientific application programs with regular computations.

Construction of exponentially fitted symplectic Runge-Kutta-Nyström methods from partitioned Runge-Kutta methods

NASA Astrophysics Data System (ADS)

Monovasilis, Theodore; Kalogiratou, Zacharoula; Simos, T. E.

2014-10-01

In this work we derive exponentially fitted symplectic Runge-Kutta-Nyström (RKN) methods from symplectic exponentially fitted partitioned Runge-Kutta (PRK) methods methods (for the approximate solution of general problems of this category see [18] - [40] and references therein). We construct RKN methods from PRK methods with up to five stages and fourth algebraic order.

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems

PubMed Central

Gao, Min; Tian, Renli; Wen, Junhao; Xiong, Qingyu; Ling, Bin; Yang, Linda

2015-01-01

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There are two characteristics of all types of shilling attacks: 1) Item abnormality: The rating of target items is always maximum or minimum; and 2) Attack promptness: It takes only a very short period time to inject attack profiles. Some papers have proposed item anomaly detection methods based on these two characteristics, but their detection rate, false alarm rate, and universality need to be further improved. To solve these problems, this paper proposes an item anomaly detection method based on dynamic partitioning for time series. This method first dynamically partitions item-rating time series based on important points. Then, we use chi square distribution (χ2) to detect abnormal intervals. The experimental results on MovieLens 100K and 1M indicate that this approach has a high detection rate and a low false alarm rate and is stable toward different attack models and filler sizes. PMID:26267477

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems.

PubMed

Gao, Min; Tian, Renli; Wen, Junhao; Xiong, Qingyu; Ling, Bin; Yang, Linda

2015-01-01

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There are two characteristics of all types of shilling attacks: 1) Item abnormality: The rating of target items is always maximum or minimum; and 2) Attack promptness: It takes only a very short period time to inject attack profiles. Some papers have proposed item anomaly detection methods based on these two characteristics, but their detection rate, false alarm rate, and universality need to be further improved. To solve these problems, this paper proposes an item anomaly detection method based on dynamic partitioning for time series. This method first dynamically partitions item-rating time series based on important points. Then, we use chi square distribution (χ2) to detect abnormal intervals. The experimental results on MovieLens 100K and 1M indicate that this approach has a high detection rate and a low false alarm rate and is stable toward different attack models and filler sizes.

Partitioning error components for accuracy-assessment of near-neighbor methods of imputation

Treesearch

Albert R. Stage; Nicholas L. Crookston

2007-01-01

Imputation is applied for two quite different purposes: to supply missing data to complete a data set for subsequent modeling analyses or to estimate subpopulation totals. Error properties of the imputed values have different effects in these two contexts. We partition errors of imputation derived from similar observation units as arising from three sources:...

Compressible fluids with Maxwell-type equations, the minimal coupling with electromagnetic field and the Stefan–Boltzmann law

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mendes, Albert C.R., E-mail: albert@fisica.ufjf.br; Takakura, Flavio I., E-mail: takakura@fisica.ufjf.br; Abreu, Everton M.C., E-mail: evertonabreu@ufrrj.br

In this work we have obtained a higher-derivative Lagrangian for a charged fluid coupled with the electromagnetic fluid and the Dirac’s constraints analysis was discussed. A set of first-class constraints fixed by noncovariant gauge condition were obtained. The path integral formalism was used to obtain the partition function for the corresponding higher-derivative Hamiltonian and the Faddeev–Popov ansatz was used to construct an effective Lagrangian. Through the partition function, a Stefan–Boltzmann type law was obtained. - Highlights: • Higher-derivative Lagrangian for a charged fluid. • Electromagnetic coupling and Dirac’s constraint analysis. • Partition function through path integral formalism. • Stefan–Boltzmann-kind lawmore » through the partition function.« less

Genetic reinforcement learning through symbiotic evolution for fuzzy controller design.

PubMed

Juang, C F; Lin, J Y; Lin, C T

2000-01-01

An efficient genetic reinforcement learning algorithm for designing fuzzy controllers is proposed in this paper. The genetic algorithm (GA) adopted in this paper is based upon symbiotic evolution which, when applied to fuzzy controller design, complements the local mapping property of a fuzzy rule. Using this Symbiotic-Evolution-based Fuzzy Controller (SEFC) design method, the number of control trials, as well as consumed CPU time, are considerably reduced when compared to traditional GA-based fuzzy controller design methods and other types of genetic reinforcement learning schemes. Moreover, unlike traditional fuzzy controllers, which partition the input space into a grid, SEFC partitions the input space in a flexible way, thus creating fewer fuzzy rules. In SEFC, different types of fuzzy rules whose consequent parts are singletons, fuzzy sets, or linear equations (TSK-type fuzzy rules) are allowed. Further, the free parameters (e.g., centers and widths of membership functions) and fuzzy rules are all tuned automatically. For the TSK-type fuzzy rule especially, which put the proposed learning algorithm in use, only the significant input variables are selected to participate in the consequent of a rule. The proposed SEFC design method has been applied to different simulated control problems, including the cart-pole balancing system, a magnetic levitation system, and a water bath temperature control system. The proposed SEFC has been verified to be efficient and superior from these control problems, and from comparisons with some traditional GA-based fuzzy systems.

Gauge-invariant expectation values of the energy of a molecule in an electromagnetic field

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandal, Anirban; Hunt, Katharine L. C.

In this paper, we show that the full Hamiltonian for a molecule in an electromagnetic field can be separated into a molecular Hamiltonian and a field Hamiltonian, both with gauge-invariant expectation values. The expectation value of the molecular Hamiltonian gives physically meaningful results for the energy of a molecule in a time-dependent applied field. In contrast, the usual partitioning of the full Hamiltonian into molecular and field terms introduces an arbitrary gauge-dependent potential into the molecular Hamiltonian and leaves a gauge-dependent form of the Hamiltonian for the field. With the usual partitioning of the Hamiltonian, this same problem of gaugemore » dependence arises even in the absence of an applied field, as we show explicitly by considering a gauge transformation from zero applied field and zero external potentials to zero applied field, but non-zero external vector and scalar potentials. We resolve this problem and also remove the gauge dependence from the Hamiltonian for a molecule in a non-zero applied field and from the field Hamiltonian, by repartitioning the full Hamiltonian. It is possible to remove the gauge dependence because the interaction of the molecular charges with the gauge potential cancels identically with a gauge-dependent term in the usual form of the field Hamiltonian. We treat the electromagnetic field classically and treat the molecule quantum mechanically, but nonrelativistically. Our derivation starts from the Lagrangian for a set of charged particles and an electromagnetic field, with the particle coordinates, the vector potential, the scalar potential, and their time derivatives treated as the variables in the Lagrangian. We construct the full Hamiltonian using a Lagrange multiplier method originally suggested by Dirac, partition this Hamiltonian into a molecular term H{sub m} and a field term H{sub f}, and show that both H{sub m} and H{sub f} have gauge-independent expectation values. Any gauge may be chosen for the calculations; but following our partitioning, the expectation values of the molecular Hamiltonian are identical to those obtained directly in the Coulomb gauge. As a corollary of this result, the power absorbed by a molecule from a time-dependent, applied electromagnetic field is equal to the time derivative of the non-adiabatic term in the molecular energy, in any gauge.« less

New Linear Partitioning Models Based on Experimental Water: Supercritical CO 2 Partitioning Data of Selected Organic Compounds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burant, Aniela; Thompson, Christopher; Lowry, Gregory V.

2016-05-17

Partitioning coefficients of organic compounds between water and supercritical CO2 (sc-CO2) are necessary to assess the risk of migration of these chemicals from subsurface CO2 storage sites. Despite the large number of potential organic contaminants, the current data set of published water-sc-CO2 partitioning coefficients is very limited. Here, the partitioning coefficients of thiophene, pyrrole, and anisole were measured in situ over a range of temperatures and pressures using a novel pressurized batch reactor system with dual spectroscopic detectors: a near infrared spectrometer for measuring the organic analyte in the CO2 phase, and a UV detector for quantifying the analyte inmore » the aqueous phase. Our measured partitioning coefficients followed expected trends based on volatility and aqueous solubility. The partitioning coefficients and literature data were then used to update a published poly-parameter linear free energy relationship and to develop five new linear free energy relationships for predicting water-sc-CO2 partitioning coefficients. Four of the models targeted a single class of organic compounds. Unlike models that utilize Abraham solvation parameters, the new relationships use vapor pressure and aqueous solubility of the organic compound at 25 °C and CO2 density to predict partitioning coefficients over a range of temperature and pressure conditions. The compound class models provide better estimates of partitioning behavior for compounds in that class than the model built for the entire dataset.« less

Multi-scale modularity and motif distributional effect in metabolic networks.

PubMed

Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

2016-01-01

Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.

Women and ethnic cleansing: a history of Partition in India and Pakistan.

PubMed

Gonzalez Manchon, B

2000-01-01

After the departure of the British, India was divided into a non-Muslim-majority state (India) and a new Muslim-majority entity (Pakistan). This territorial separation of religious communities emerged as the political solution to communal tensions and Muslim claims for a separate state. In this paper, the books ¿Borders and Boundaries: Women in India's Partition¿ by Ritu Menon and Kamla Bhasin and ¿The Other Side of Silence: Voices from the Partition of India¿ by Urvashi Butalia are reviewed. It is noted that these books establish the links between historical Partition events, their dramatic consequences for women, and the reflections of past divisions in the context of more contemporary realities. Overall, from the thoughtful interpretation of the Partition events provided by these books, it is concluded that the division has far from provided appropriate solutions to outstanding problems. It has also been responsible for creating great human distress, but also for inducing the emergence of even more complex issues around the nationalist question.

A Formal Model of Partitioning for Integrated Modular Avionics

NASA Technical Reports Server (NTRS)

DiVito, Ben L.

1998-01-01

The aviation industry is gradually moving toward the use of integrated modular avionics (IMA) for civilian transport aircraft. An important concern for IMA is ensuring that applications are safely partitioned so they cannot interfere with one another. We have investigated the problem of ensuring safe partitioning and logical non-interference among separate applications running on a shared Avionics Computer Resource (ACR). This research was performed in the context of ongoing standardization efforts, in particular, the work of RTCA committee SC-182, and the recently completed ARINC 653 application executive (APEX) interface standard. We have developed a formal model of partitioning suitable for evaluating the design of an ACR. The model draws from the mathematical modeling techniques developed by the computer security community. This report presents a formulation of partitioning requirements expressed first using conventional mathematical notation, then formalized using the language of SRI'S Prototype Verification System (PVS). The approach is demonstrated on three candidate designs, each an abstraction of features found in real systems.

A stable partitioned FSI algorithm for incompressible flow and deforming beams

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, L., E-mail: lil19@rpi.edu; Henshaw, W.D., E-mail: henshw@rpi.edu; Banks, J.W., E-mail: banksj3@rpi.edu

2016-05-01

An added-mass partitioned (AMP) algorithm is described for solving fluid–structure interaction (FSI) problems coupling incompressible flows with thin elastic structures undergoing finite deformations. The new AMP scheme is fully second-order accurate and stable, without sub-time-step iterations, even for very light structures when added-mass effects are strong. The fluid, governed by the incompressible Navier–Stokes equations, is solved in velocity-pressure form using a fractional-step method; large deformations are treated with a mixed Eulerian-Lagrangian approach on deforming composite grids. The motion of the thin structure is governed by a generalized Euler–Bernoulli beam model, and these equations are solved in a Lagrangian frame usingmore » two approaches, one based on finite differences and the other on finite elements. The key AMP interface condition is a generalized Robin (mixed) condition on the fluid pressure. This condition, which is derived at a continuous level, has no adjustable parameters and is applied at the discrete level to couple the partitioned domain solvers. Special treatment of the AMP condition is required to couple the finite-element beam solver with the finite-difference-based fluid solver, and two coupling approaches are described. A normal-mode stability analysis is performed for a linearized model problem involving a beam separating two fluid domains, and it is shown that the AMP scheme is stable independent of the ratio of the mass of the fluid to that of the structure. A traditional partitioned (TP) scheme using a Dirichlet–Neumann coupling for the same model problem is shown to be unconditionally unstable if the added mass of the fluid is too large. A series of benchmark problems of increasing complexity are considered to illustrate the behavior of the AMP algorithm, and to compare the behavior with that of the TP scheme. The results of all these benchmark problems verify the stability and accuracy of the AMP scheme. Results for one benchmark problem modeling blood flow in a deforming artery are also compared with corresponding results available in the literature.« less

Recursions for the exchangeable partition function of the seedbank coalescent.

PubMed

Kurt, Noemi; Rafler, Mathias

2017-04-01

For the seedbank coalescent with mutation under the infinite alleles assumption, which describes the gene genealogy of a population with a strong seedbank effect subject to mutations, we study the distribution of the final partition with mutation. This generalizes the coalescent with freeze by Dong et al. (2007) to coalescents where ancestral lineages are blocked from coalescing. We derive an implicit recursion which we show to have a unique solution and give an interpretation in terms of absorption problems of a random walk. Moreover, we derive recursions for the distribution of the number of blocks in the final partition. Copyright © 2017 Elsevier Inc. All rights reserved.

Surveillance system and method having parameter estimation and operating mode partitioning

NASA Technical Reports Server (NTRS)

Bickford, Randall L. (Inventor)

2003-01-01

A system and method for monitoring an apparatus or process asset including partitioning an unpartitioned training data set into a plurality of training data subsets each having an operating mode associated thereto; creating a process model comprised of a plurality of process submodels each trained as a function of at least one of the training data subsets; acquiring a current set of observed signal data values from the asset; determining an operating mode of the asset for the current set of observed signal data values; selecting a process submodel from the process model as a function of the determined operating mode of the asset; calculating a current set of estimated signal data values from the selected process submodel for the determined operating mode; and outputting the calculated current set of estimated signal data values for providing asset surveillance and/or control.

S-HARP: A parallel dynamic spectral partitioner

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sohn, A.; Simon, H.

1998-01-01

Computational science problems with adaptive meshes involve dynamic load balancing when implemented on parallel machines. This dynamic load balancing requires fast partitioning of computational meshes at run time. The authors present in this report a fast parallel dynamic partitioner, called S-HARP. The underlying principles of S-HARP are the fast feature of inertial partitioning and the quality feature of spectral partitioning. S-HARP partitions a graph from scratch, requiring no partition information from previous iterations. Two types of parallelism have been exploited in S-HARP, fine grain loop level parallelism and coarse grain recursive parallelism. The parallel partitioner has been implemented in Messagemore » Passing Interface on Cray T3E and IBM SP2 for portability. Experimental results indicate that S-HARP can partition a mesh of over 100,000 vertices into 256 partitions in 0.2 seconds on a 64 processor Cray T3E. S-HARP is much more scalable than other dynamic partitioners, giving over 15 fold speedup on 64 processors while ParaMeTiS1.0 gives a few fold speedup. Experimental results demonstrate that S-HARP is three to 10 times faster than the dynamic partitioners ParaMeTiS and Jostle on six computational meshes of size over 100,000 vertices.« less

Two dissimilar approaches to dynamical systems on hyper MV -algebras and their information entropy

NASA Astrophysics Data System (ADS)

Mehrpooya, Adel; Ebrahimi, Mohammad; Davvaz, Bijan

2017-09-01

Measuring the flow of information that is related to the evolution of a system which is modeled by applying a mathematical structure is of capital significance for science and usually for mathematics itself. Regarding this fact, a major issue in concern with hyperstructures is their dynamics and the complexity of the varied possible dynamics that exist over them. Notably, the dynamics and uncertainty of hyper MV -algebras which are hyperstructures and extensions of a central tool in infinite-valued Lukasiewicz propositional calculus that models many valued logics are of primary concern. Tackling this problem, in this paper we focus on the subject of dynamical systems on hyper MV -algebras and their entropy. In this respect, we adopt two varied approaches. One is the set-based approach in which hyper MV -algebra dynamical systems are developed by employing set functions and set partitions. By the other method that is based on points and point partitions, we establish the concept of hyper injective dynamical systems on hyper MV -algebras. Next, we study the notion of entropy for both kinds of systems. Furthermore, we consider essential ergodic characteristics of those systems and their entropy. In particular, we introduce the concept of isomorphic hyper injective and hyper MV -algebra dynamical systems, and we demonstrate that isomorphic systems have the same entropy. We present a couple of theorems in order to help calculate entropy. In particular, we prove a contemporary version of addition and Kolmogorov-Sinai Theorems. Furthermore, we provide a comparison between the indispensable properties of hyper injective and semi-independent dynamical systems. Specifically, we present and prove theorems that draw comparisons between the entropies of such systems. Lastly, we discuss some possible relationships between the theories of hyper MV -algebra and MV -algebra dynamical systems.

Computer-based creativity enhanced conceptual design model for non-routine design of mechanical systems

NASA Astrophysics Data System (ADS)

Li, Yutong; Wang, Yuxin; Duffy, Alex H. B.

2014-11-01

Computer-based conceptual design for routine design has made great strides, yet non-routine design has not been given due attention, and it is still poorly automated. Considering that the function-behavior-structure(FBS) model is widely used for modeling the conceptual design process, a computer-based creativity enhanced conceptual design model(CECD) for non-routine design of mechanical systems is presented. In the model, the leaf functions in the FBS model are decomposed into and represented with fine-grain basic operation actions(BOA), and the corresponding BOA set in the function domain is then constructed. Choosing building blocks from the database, and expressing their multiple functions with BOAs, the BOA set in the structure domain is formed. Through rule-based dynamic partition of the BOA set in the function domain, many variants of regenerated functional schemes are generated. For enhancing the capability to introduce new design variables into the conceptual design process, and dig out more innovative physical structure schemes, the indirect function-structure matching strategy based on reconstructing the combined structure schemes is adopted. By adjusting the tightness of the partition rules and the granularity of the divided BOA subsets, and making full use of the main function and secondary functions of each basic structure in the process of reconstructing of the physical structures, new design variables and variants are introduced into the physical structure scheme reconstructing process, and a great number of simpler physical structure schemes to accomplish the overall function organically are figured out. The creativity enhanced conceptual design model presented has a dominant capability in introducing new deign variables in function domain and digging out simpler physical structures to accomplish the overall function, therefore it can be utilized to solve non-routine conceptual design problem.

A Combined Approach to Cartographic Displacement for Buildings Based on Skeleton and Improved Elastic Beam Algorithm

PubMed Central

Liu, Yuangang; Guo, Qingsheng; Sun, Yageng; Ma, Xiaoya

2014-01-01

Scale reduction from source to target maps inevitably leads to conflicts of map symbols in cartography and geographic information systems (GIS). Displacement is one of the most important map generalization operators and it can be used to resolve the problems that arise from conflict among two or more map objects. In this paper, we propose a combined approach based on constraint Delaunay triangulation (CDT) skeleton and improved elastic beam algorithm for automated building displacement. In this approach, map data sets are first partitioned. Then the displacement operation is conducted in each partition as a cyclic and iterative process of conflict detection and resolution. In the iteration, the skeleton of the gap spaces is extracted using CDT. It then serves as an enhanced data model to detect conflicts and construct the proximity graph. Then, the proximity graph is adjusted using local grouping information. Under the action of forces derived from the detected conflicts, the proximity graph is deformed using the improved elastic beam algorithm. In this way, buildings are displaced to find an optimal compromise between related cartographic constraints. To validate this approach, two topographic map data sets (i.e., urban and suburban areas) were tested. The results were reasonable with respect to each constraint when the density of the map was not extremely high. In summary, the improvements include (1) an automated parameter-setting method for elastic beams, (2) explicit enforcement regarding the positional accuracy constraint, added by introducing drag forces, (3) preservation of local building groups through displacement over an adjusted proximity graph, and (4) an iterative strategy that is more likely to resolve the proximity conflicts than the one used in the existing elastic beam algorithm. PMID:25470727

Applying graph partitioning methods in measurement-based dynamic load balancing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhatele, Abhinav; Fourestier, Sebastien; Menon, Harshitha

Load imbalance leads to an increasing waste of resources as an application is scaled to more and more processors. Achieving the best parallel efficiency for a program requires optimal load balancing which is a NP-hard problem. However, finding near-optimal solutions to this problem for complex computational science and engineering applications is becoming increasingly important. Charm++, a migratable objects based programming model, provides a measurement-based dynamic load balancing framework. This framework instruments and then migrates over-decomposed objects to balance computational load and communication at runtime. This paper explores the use of graph partitioning algorithms, traditionally used for partitioning physical domains/meshes, formore » measurement-based dynamic load balancing of parallel applications. In particular, we present repartitioning methods developed in a graph partitioning toolbox called SCOTCH that consider the previous mapping to minimize migration costs. We also discuss a new imbalance reduction algorithm for graphs with irregular load distributions. We compare several load balancing algorithms using microbenchmarks on Intrepid and Ranger and evaluate the effect of communication, number of cores and number of objects on the benefit achieved from load balancing. New algorithms developed in SCOTCH lead to better performance compared to the METIS partitioners for several cases, both in terms of the application execution time and fewer number of objects migrated.« less

Euclid, Fibonacci, Sketchpad.

ERIC Educational Resources Information Center

Litchfield, Daniel C.; Goldenheim, David A.

1997-01-01

Describes the solution to a geometric problem by two ninth-grade mathematicians using The Geometer's Sketchpad computer software program. The problem was to divide any line segment into a regular partition of any number of parts, a variation on a problem by Euclid. The solution yielded two constructions, one a GLaD construction and the other using…

A duality principle for the multi-block entanglement entropy of free fermion systems.

PubMed

Carrasco, J A; Finkel, F; González-López, A; Tempesta, P

2017-09-11

The analysis of the entanglement entropy of a subsystem of a one-dimensional quantum system is a powerful tool for unravelling its critical nature. For instance, the scaling behaviour of the entanglement entropy determines the central charge of the associated Virasoro algebra. For a free fermion system, the entanglement entropy depends essentially on two sets, namely the set A of sites of the subsystem considered and the set K of excited momentum modes. In this work we make use of a general duality principle establishing the invariance of the entanglement entropy under exchange of the sets A and K to tackle complex problems by studying their dual counterparts. The duality principle is also a key ingredient in the formulation of a novel conjecture for the asymptotic behavior of the entanglement entropy of a free fermion system in the general case in which both sets A and K consist of an arbitrary number of blocks. We have verified that this conjecture reproduces the numerical results with excellent precision for all the configurations analyzed. We have also applied the conjecture to deduce several asymptotic formulas for the mutual and r-partite information generalizing the known ones for the single block case.

An extended affinity propagation clustering method based on different data density types.

PubMed

Zhao, XiuLi; Xu, WeiXiang

2015-01-01

Affinity propagation (AP) algorithm, as a novel clustering method, does not require the users to specify the initial cluster centers in advance, which regards all data points as potential exemplars (cluster centers) equally and groups the clusters totally by the similar degree among the data points. But in many cases there exist some different intensive areas within the same data set, which means that the data set does not distribute homogeneously. In such situation the AP algorithm cannot group the data points into ideal clusters. In this paper, we proposed an extended AP clustering algorithm to deal with such a problem. There are two steps in our method: firstly the data set is partitioned into several data density types according to the nearest distances of each data point; and then the AP clustering method is, respectively, used to group the data points into clusters in each data density type. Two experiments are carried out to evaluate the performance of our algorithm: one utilizes an artificial data set and the other uses a real seismic data set. The experiment results show that groups are obtained more accurately by our algorithm than OPTICS and AP clustering algorithm itself.

A stable partitioned FSI algorithm for rigid bodies and incompressible flow. Part I: Model problem analysis

NASA Astrophysics Data System (ADS)

Banks, J. W.; Henshaw, W. D.; Schwendeman, D. W.; Tang, Qi

2017-08-01

A stable partitioned algorithm is developed for fluid-structure interaction (FSI) problems involving viscous incompressible flow and rigid bodies. This added-mass partitioned (AMP) algorithm remains stable, without sub-iterations, for light and even zero mass rigid bodies when added-mass and viscous added-damping effects are large. The scheme is based on a generalized Robin interface condition for the fluid pressure that includes terms involving the linear acceleration and angular acceleration of the rigid body. Added-mass effects are handled in the Robin condition by inclusion of a boundary integral term that depends on the pressure. Added-damping effects due to the viscous shear forces on the body are treated by inclusion of added-damping tensors that are derived through a linearization of the integrals defining the force and torque. Added-damping effects may be important at low Reynolds number, or, for example, in the case of a rotating cylinder or rotating sphere when the rotational moments of inertia are small. In this first part of a two-part series, the properties of the AMP scheme are motivated and evaluated through the development and analysis of some model problems. The analysis shows when and why the traditional partitioned scheme becomes unstable due to either added-mass or added-damping effects. The analysis also identifies the proper form of the added-damping which depends on the discrete time-step and the grid-spacing normal to the rigid body. The results of the analysis are confirmed with numerical simulations that also demonstrate a second-order accurate implementation of the AMP scheme.

Energy Partitioning of Seismic Phases: Current Datasets and Techniques Aimed at Improving the Future of Event Identification

NASA Astrophysics Data System (ADS)

Bonner, J.

2006-05-01

Differences in energy partitioning of seismic phases from earthquakes and explosions provide the opportunity for event identification. In this talk, I will briefly review teleseismic Ms:mb and P/S ratio techniques that help identify events based on differences in compressional, shear, and surface wave energy generation from explosions and earthquakes. With the push to identify smaller yield explosions, the identification process has become increasingly complex as varied types of explosions, including chemical, mining, and nuclear, must be identified at regional distances. Thus, I will highlight some of the current views and problems associated with the energy partitioning of seismic phases from single- and delay-fired chemical explosions. One problem yet to have a universally accepted answer is whether the explosion and earthquake populations, based on the Ms:mb discriminants, should be separated at smaller magnitudes. I will briefly describe the datasets and theory that support either converging or parallel behavior of these populations. Also, I will discuss improvement to the currently used methods that will better constrain this problem in the future. I will also discuss the role of regional P/S ratios in identifying explosions. In particular, recent datasets from South Africa, Scandinavia, and the Western United States collected from earthquakes, single-fired chemical explosions, and/or delay-fired mining explosions have provide new insight into regional P, S, Lg, and Rg energy partitioning. Data from co-located mining and chemical explosions suggest that some mining explosions may be used for limited calibration of regional discriminants in regions where no historic explosion data is available.

Data Clustering

NASA Astrophysics Data System (ADS)

Wagstaff, Kiri L.

2012-03-01

On obtaining a new data set, the researcher is immediately faced with the challenge of obtaining a high-level understanding from the observations. What does a typical item look like? What are the dominant trends? How many distinct groups are included in the data set, and how is each one characterized? Which observable values are common, and which rarely occur? Which items stand out as anomalies or outliers from the rest of the data? This challenge is exacerbated by the steady growth in data set size [11] as new instruments push into new frontiers of parameter space, via improvements in temporal, spatial, and spectral resolution, or by the desire to "fuse" observations from different modalities and instruments into a larger-picture understanding of the same underlying phenomenon. Data clustering algorithms provide a variety of solutions for this task. They can generate summaries, locate outliers, compress data, identify dense or sparse regions of feature space, and build data models. It is useful to note up front that "clusters" in this context refer to groups of items within some descriptive feature space, not (necessarily) to "galaxy clusters" which are dense regions in physical space. The goal of this chapter is to survey a variety of data clustering methods, with an eye toward their applicability to astronomical data analysis. In addition to improving the individual researcher’s understanding of a given data set, clustering has led directly to scientific advances, such as the discovery of new subclasses of stars [14] and gamma-ray bursts (GRBs) [38]. All clustering algorithms seek to identify groups within a data set that reflect some observed, quantifiable structure. Clustering is traditionally an unsupervised approach to data analysis, in the sense that it operates without any direct guidance about which items should be assigned to which clusters. There has been a recent trend in the clustering literature toward supporting semisupervised or constrained clustering, in which some partial information about item assignments or other components of the resulting output are already known and must be accommodated by the solution. Some algorithms seek a partition of the data set into distinct clusters, while others build a hierarchy of nested clusters that can capture taxonomic relationships. Some produce a single optimal solution, while others construct a probabilistic model of cluster membership. More formally, clustering algorithms operate on a data set X composed of items represented by one or more features (dimensions). These could include physical location, such as right ascension and declination, as well as other properties such as brightness, color, temporal change, size, texture, and so on. Let D be the number of dimensions used to represent each item, xi ∈ RD. The clustering goal is to produce an organization P of the items in X that optimizes an objective function f : P -> R, which quantifies the quality of solution P. Often f is defined so as to maximize similarity within a cluster and minimize similarity between clusters. To that end, many algorithms make use of a measure d : X x X -> R of the distance between two items. A partitioning algorithm produces a set of clusters P = {c1, . . . , ck} such that the clusters are nonoverlapping (c_i intersected with c_j = empty set, i != j) subsets of the data set (Union_i c_i=X). Hierarchical algorithms produce a series of partitions P = {p1, . . . , pn }. For a complete hierarchy, the number of partitions n’= n, the number of items in the data set; the top partition is a single cluster containing all items, and the bottom partition contains n clusters, each containing a single item. For model-based clustering, each cluster c_j is represented by a model m_j , such as the cluster center or a Gaussian distribution. The wide array of available clustering algorithms may seem bewildering, and covering all of them is beyond the scope of this chapter. Choosing among them for a particular application involves considerations of the kind of data being analyzed, algorithm runtime efficiency, and how much prior knowledge is available about the problem domain, which can dictate the nature of clusters sought. Fundamentally, the clustering method and its representations of clusters carries with it a definition of what a cluster is, and it is important that this be aligned with the analysis goals for the problem at hand. In this chapter, I emphasize this point by identifying for each algorithm the cluster representation as a model, m_j , even for algorithms that are not typically thought of as creating a “model.” This chapter surveys a basic collection of clustering methods useful to any practitioner who is interested in applying clustering to a new data set. The algorithms include k-means (Section 25.2), EM (Section 25.3), agglomerative (Section 25.4), and spectral (Section 25.5) clustering, with side mentions of variants such as kernel k-means and divisive clustering. The chapter also discusses each algorithm’s strengths and limitations and provides pointers to additional in-depth reading for each subject. Section 25.6 discusses methods for incorporating domain knowledge into the clustering process. This chapter concludes with a brief survey of interesting applications of clustering methods to astronomy data (Section 25.7). The chapter begins with k-means because it is both generally accessible and so widely used that understanding it can be considered a necessary prerequisite for further work in the field. EM can be viewed as a more sophisticated version of k-means that uses a generative model for each cluster and probabilistic item assignments. Agglomerative clustering is the most basic form of hierarchical clustering and provides a basis for further exploration of algorithms in that vein. Spectral clustering permits a departure from feature-vector-based clustering and can operate on data sets instead represented as affinity, or similarity matrices—cases in which only pairwise information is known. The list of algorithms covered in this chapter is representative of those most commonly in use, but it is by no means comprehensive. There is an extensive collection of existing books on clustering that provide additional background and depth. Three early books that remain useful today are Anderberg’s Cluster Analysis for Applications [3], Hartigan’s Clustering Algorithms [25], and Gordon’s Classification [22]. The latter covers basics on similarity measures, partitioning and hierarchical algorithms, fuzzy clustering, overlapping clustering, conceptual clustering, validations methods, and visualization or data reduction techniques such as principal components analysis (PCA),multidimensional scaling, and self-organizing maps. More recently, Jain et al. provided a useful and informative survey [27] of a variety of different clustering algorithms, including those mentioned here as well as fuzzy, graph-theoretic, and evolutionary clustering. Everitt’s Cluster Analysis [19] provides a modern overview of algorithms, similarity measures, and evaluation methods.

Cylindric partitions, {{\\boldsymbol{ W }}}_{r} characters and the Andrews-Gordon-Bressoud identities

NASA Astrophysics Data System (ADS)

Foda, O.; Welsh, T. A.

2016-04-01

We study the Andrews-Gordon-Bressoud (AGB) generalisations of the Rogers-Ramanujan q-series identities in the context of cylindric partitions. We recall the definition of r-cylindric partitions, and provide a simple proof of Borodin’s product expression for their generating functions, that can be regarded as a limiting case of an unpublished proof by Krattenthaler. We also recall the relationships between the r-cylindric partition generating functions, the principal characters of {\\hat{{sl}}}r algebras, the {{\\boldsymbol{ M }}}r r,r+d minimal model characters of {{\\boldsymbol{ W }}}r algebras, and the r-string abaci generating functions, providing simple proofs for each. We then set r = 2, and use two-cylindric partitions to re-derive the AGB identities as follows. Firstly, we use Borodin’s product expression for the generating functions of the two-cylindric partitions with infinitely long parts, to obtain the product sides of the AGB identities, times a factor {(q;q)}∞ -1, which is the generating function of ordinary partitions. Next, we obtain a bijection from the two-cylindric partitions, via two-string abaci, into decorated versions of Bressoud’s restricted lattice paths. Extending Bressoud’s method of transforming between restricted paths that obey different restrictions, we obtain sum expressions with manifestly non-negative coefficients for the generating functions of the two-cylindric partitions which contains a factor {(q;q)}∞ -1. Equating the product and sum expressions of the same two-cylindric partitions, and canceling a factor of {(q;q)}∞ -1 on each side, we obtain the AGB identities.

Common y-intercept and single compound regressions of gas-particle partitioning data vs 1/T

NASA Astrophysics Data System (ADS)

Pankow, James F.

Confidence intervals are placed around the log Kp vs 1/ T correlation equations obtained using simple linear regressions (SLR) with the gas-particle partitioning data set of Yamasaki et al. [(1982) Env. Sci. Technol.16, 189-194]. The compounds and groups of compounds studied include the polycylic aromatic hydrocarbons phenanthrene + anthracene, me-phenanthrene + me-anthracene, fluoranthene, pyrene, benzo[ a]fluorene + benzo[ b]fluorene, chrysene + benz[ a]anthracene + triphenylene, benzo[ b]fluoranthene + benzo[ k]fluoranthene, and benzo[ a]pyrene + benzo[ e]pyrene (note: me = methyl). For any given compound, at equilibrium, the partition coefficient Kp equals ( F/ TSP)/ A where F is the particulate-matter associated concentration (ng m -3), A is the gas-phase concentration (ng m -3), and TSP is the concentration of particulate matter (μg m -3). At temperatures more than 10°C from the mean sampling temperature of 17°C, the confidence intervals are quite wide. Since theory predicts that similar compounds sorbing on the same particulate matter should possess very similar y-intercepts, the data set was also fitted using a special common y-intercept regression (CYIR). For most of the compounds, the CYIR equations fell inside of the SLR 95% confidence intervals. The CYIR y-intercept value is -18.48, and is reasonably close to the type of value that can be predicted for PAH compounds. The set of CYIR regression equations is probably more reliable than the set of SLR equations. For example, the CYIR-derived desorption enthalpies are much more highly correlated with vaporization enthalpies than are the SLR-derived desorption enthalpies. It is recommended that the CYIR approach be considered whenever analysing temperature-dependent gas-particle partitioning data.

What are the structural features that drive partitioning of proteins in aqueous two-phase systems?

PubMed

Wu, Zhonghua; Hu, Gang; Wang, Kui; Zaslavsky, Boris Yu; Kurgan, Lukasz; Uversky, Vladimir N

2017-01-01

Protein partitioning in aqueous two-phase systems (ATPSs) represents a convenient, inexpensive, and easy to scale-up protein separation technique. Since partition behavior of a protein dramatically depends on an ATPS composition, it would be highly beneficial to have reliable means for (even qualitative) prediction of partitioning of a target protein under different conditions. Our aim was to understand which structural features of proteins contribute to partitioning of a query protein in a given ATPS. We undertook a systematic empirical analysis of relations between 57 numerical structural descriptors derived from the corresponding amino acid sequences and crystal structures of 10 well-characterized proteins and the partition behavior of these proteins in 29 different ATPSs. This analysis revealed that just a few structural characteristics of proteins can accurately determine behavior of these proteins in a given ATPS. However, partition behavior of proteins in different ATPSs relies on different structural features. In other words, we could not find a unique set of protein structural features derived from their crystal structures that could be used for the description of the protein partition behavior of all proteins in all ATPSs analyzed in this study. We likely need to gain better insight into relationships between protein-solvent interactions and protein structure peculiarities, in particular given limitations of the used here crystal structures, to be able to construct a model that accurately predicts protein partition behavior across all ATPSs. Copyright © 2016 Elsevier B.V. All rights reserved.

Spectral Upscaling for Graph Laplacian Problems with Application to Reservoir Simulation

DOE PAGES

Barker, Andrew T.; Lee, Chak S.; Vassilevski, Panayot S.

2017-10-26

Here, we consider coarsening procedures for graph Laplacian problems written in a mixed saddle-point form. In that form, in addition to the original (vertex) degrees of freedom (dofs), we also have edge degrees of freedom. We extend previously developed aggregation-based coarsening procedures applied to both sets of dofs to now allow more than one coarse vertex dof per aggregate. Those dofs are selected as certain eigenvectors of local graph Laplacians associated with each aggregate. Additionally, we coarsen the edge dofs by using traces of the discrete gradients of the already constructed coarse vertex dofs. These traces are defined on themore » interface edges that connect any two adjacent aggregates. The overall procedure is a modification of the spectral upscaling procedure developed in for the mixed finite element discretization of diffusion type PDEs which has the important property of maintaining inf-sup stability on coarse levels and having provable approximation properties. We consider applications to partitioning a general graph and to a finite volume discretization interpreted as a graph Laplacian, developing consistent and accurate coarse-scale models of a fine-scale problem.« less

Semi-implicit time integration of atmospheric flows with characteristic-based flux partitioning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghosh, Debojyoti; Constantinescu, Emil M.

2016-06-23

Here, this paper presents a characteristic-based flux partitioning for the semi-implicit time integration of atmospheric flows. Nonhydrostatic models require the solution of the compressible Euler equations. The acoustic time scale is significantly faster than the advective scale, yet it is typically not relevant to atmospheric and weather phenomena. The acoustic and advective components of the hyperbolic flux are separated in the characteristic space. High-order, conservative additive Runge-Kutta methods are applied to the partitioned equations so that the acoustic component is integrated in time implicitly with an unconditionally stable method, while the advective component is integrated explicitly. The time step ofmore » the overall algorithm is thus determined by the advective scale. Benchmark flow problems are used to demonstrate the accuracy, stability, and convergence of the proposed algorithm. The computational cost of the partitioned semi-implicit approach is compared with that of explicit time integration.« less

Significant Scales in Community Structure

NASA Astrophysics Data System (ADS)

Traag, V. A.; Krings, G.; van Dooren, P.

2013-10-01

Many complex networks show signs of modular structure, uncovered by community detection. Although many methods succeed in revealing various partitions, it remains difficult to detect at what scale some partition is significant. This problem shows foremost in multi-resolution methods. We here introduce an efficient method for scanning for resolutions in one such method. Additionally, we introduce the notion of ``significance'' of a partition, based on subgraph probabilities. Significance is independent of the exact method used, so could also be applied in other methods, and can be interpreted as the gain in encoding a graph by making use of a partition. Using significance, we can determine ``good'' resolution parameters, which we demonstrate on benchmark networks. Moreover, optimizing significance itself also shows excellent performance. We demonstrate our method on voting data from the European Parliament. Our analysis suggests the European Parliament has become increasingly ideologically divided and that nationality plays no role.

Control of ingot quality and solar cell appearance of cast mono-like silicon by using seed partitions

NASA Astrophysics Data System (ADS)

Lan, C. Y.; Wu, Y. C.; Lan, A.; Yang, C. F.; Hsu, C.; Lu, C. M.; Yang, A.; Lan, C. W.

2017-10-01

The growth of mono-like ingot by directional solidification has suffered serious problems in defect control. We proposed a simple approach by using seed partitions, and the grown crystal had much lower defects and better orientation uniformity. Furthermore, the partitions allowed the much easier seed preparation, which had a significant advantage in production. The concept was demonstrated by a G1 experiment, and the detailed defect analyses were carried out. The wafers after gettering had the best lifetime of more than 1 ms after surface passivation. The color mismatch in the appearance of the solar cells made from the wafer was also significantly mitigated.

Covariance Partition Priors: A Bayesian Approach to Simultaneous Covariance Estimation for Longitudinal Data.

PubMed

Gaskins, J T; Daniels, M J

2016-01-02

The estimation of the covariance matrix is a key concern in the analysis of longitudinal data. When data consists of multiple groups, it is often assumed the covariance matrices are either equal across groups or are completely distinct. We seek methodology to allow borrowing of strength across potentially similar groups to improve estimation. To that end, we introduce a covariance partition prior which proposes a partition of the groups at each measurement time. Groups in the same set of the partition share dependence parameters for the distribution of the current measurement given the preceding ones, and the sequence of partitions is modeled as a Markov chain to encourage similar structure at nearby measurement times. This approach additionally encourages a lower-dimensional structure of the covariance matrices by shrinking the parameters of the Cholesky decomposition toward zero. We demonstrate the performance of our model through two simulation studies and the analysis of data from a depression study. This article includes Supplementary Material available online.

Hydraulic geometry of the Platte River in south-central Nebraska

USGS Publications Warehouse

Eschner, T.R.

1982-01-01

At-a-station hydraulic-geometry of the Platte River in south-central Nebraska is complex. The range of exponents of simple power-function relations is large, both between different reaches of the river, and among different sections within a given reach. The at-a-station exponents plot in several fields of the b-f-m diagram, suggesting that morphologic and hydraulic changes with increasing discharge vary considerably. Systematic changes in the plotting positions of the exponents with time indicate that in general, the width exponent has decreased, although trends are not readily apparent in the other exponents. Plots of the hydraulic-geometry relations indicate that simple power functions are not the proper model in all instances. For these sections, breaks in the slopes of the hydraulic geometry relations serve to partition the data sets. Power functions fit separately to the partitioned data described the width-, depth-, and velocity-discharge relations more accurately than did a single power function. Plotting positions of the exponents from hydraulic geometry relations of partitioned data sets on b-f-m diagrams indicate that much of the apparent variations of plotting positions of single power functions results because the single power functions compromise both subsets of partitioned data. For several sections, the shape of the channel primarily accounts for the better fit of two-power functions to partitioned data than a single power function over the entire range of data. These non-log linear relations may have significance for channel maintenance. (USGS)

Strict Constraint Feasibility in Analysis and Design of Uncertain Systems

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Giesy, Daniel P.; Kenny, Sean P.

2006-01-01

This paper proposes a methodology for the analysis and design optimization of models subject to parametric uncertainty, where hard inequality constraints are present. Hard constraints are those that must be satisfied for all parameter realizations prescribed by the uncertainty model. Emphasis is given to uncertainty models prescribed by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles. These models make it possible to consider sets of parameters having comparable as well as dissimilar levels of uncertainty. Two alternative formulations for hyper-rectangular sets are proposed, one based on a transformation of variables and another based on an infinity norm approach. The suite of tools developed enable us to determine if the satisfaction of hard constraints is feasible by identifying critical combinations of uncertain parameters. Since this practice is performed without sampling or partitioning the parameter space, the resulting assessments of robustness are analytically verifiable. Strategies that enable the comparison of the robustness of competing design alternatives, the approximation of the robust design space, and the systematic search for designs with improved robustness characteristics are also proposed. Since the problem formulation is generic and the solution methods only require standard optimization algorithms for their implementation, the tools developed are applicable to a broad range of problems in several disciplines.

A Bayesian partition modelling approach to resolve spatial variability in climate records from borehole temperature inversion

NASA Astrophysics Data System (ADS)

Hopcroft, Peter O.; Gallagher, Kerry; Pain, Christopher C.

2009-08-01

Collections of suitably chosen borehole profiles can be used to infer large-scale trends in ground-surface temperature (GST) histories for the past few hundred years. These reconstructions are based on a large database of carefully selected borehole temperature measurements from around the globe. Since non-climatic thermal influences are difficult to identify, representative temperature histories are derived by averaging individual reconstructions to minimize the influence of these perturbing factors. This may lead to three potentially important drawbacks: the net signal of non-climatic factors may not be zero, meaning that the average does not reflect the best estimate of past climate; the averaging over large areas restricts the useful amount of more local climate change information available; and the inversion methods used to reconstruct the past temperatures at each site must be mathematically identical and are therefore not necessarily best suited to all data sets. In this work, we avoid these issues by using a Bayesian partition model (BPM), which is computed using a trans-dimensional form of a Markov chain Monte Carlo algorithm. This then allows the number and spatial distribution of different GST histories to be inferred from a given set of borehole data by partitioning the geographical area into discrete partitions. Profiles that are heavily influenced by non-climatic factors will be partitioned separately. Conversely, profiles with climatic information, which is consistent with neighbouring profiles, will then be inferred to lie in the same partition. The geographical extent of these partitions then leads to information on the regional extent of the climatic signal. In this study, three case studies are described using synthetic and real data. The first demonstrates that the Bayesian partition model method is able to correctly partition a suite of synthetic profiles according to the inferred GST history. In the second, more realistic case, a series of temperature profiles are calculated using surface air temperatures of a global climate model simulation. In the final case, 23 real boreholes from the United Kingdom, previously used for climatic reconstructions, are examined and the results compared with a local instrumental temperature series and the previous estimate derived from the same borehole data. The results indicate that the majority (17) of the 23 boreholes are unsuitable for climatic reconstruction purposes, at least without including other thermal processes in the forward model.

Crystal-chemistry and partitioning of REE in whitlockite

NASA Technical Reports Server (NTRS)

Colson, R. O.; Jolliff, B. L.

1993-01-01

Partitioning of Rare Earth Elements (REE) in whitlockite is complicated by the fact that two or more charge-balancing substitutions are involved and by the fact that concentrations of REE in natural whitlockites are sufficiently high such that simple partition coefficients are not expected to be constant even if mixing in the system is completely ideal. The present study combines preexisting REE partitioning data in whitlockites with new experiments in the same compositional system and at the same temperature (approximately 1030 C) to place additional constraints on the complex variations of REE partition coefficients and to test theoretical models for how REE partitioning should vary with REE concentration and other compositional variables. With this data set, and by combining crystallographic and thermochemical constraints with a SAS simultaneous-equation best-fitting routine, it is possible to infer answers to the following questions: what is the speciation on the individual sites Ca(B), Mg, and Ca(IIA) (where the ideal structural formula is Ca(B)18 Mg2Ca(IIA)2P14O56); how are REE's charge-balanced in the crystal; and is mixing of REE in whitlockite ideal or non-ideal. This understanding is necessary in order to extrapolate derived partition coefficients to other compositional systems and provides a broadened understanding of the crystal chemistry of whitlockite.

Cluster formation and drag reduction-proposed mechanism of particle recirculation within the partition column of the bottom spray fluid-bed coater.

PubMed

Wang, Li Kun; Heng, Paul Wan Sia; Liew, Celine Valeria

2015-04-01

Bottom spray fluid-bed coating is a common technique for coating multiparticulates. Under the quality-by-design framework, particle recirculation within the partition column is one of the main variability sources affecting particle coating and coat uniformity. However, the occurrence and mechanism of particle recirculation within the partition column of the coater are not well understood. The purpose of this study was to visualize and define particle recirculation within the partition column. Based on different combinations of partition gap setting, air accelerator insert diameter, and particle size fraction, particle movements within the partition column were captured using a high-speed video camera. The particle recirculation probability and voidage information were mapped using a visiometric process analyzer. High-speed images showed that particles contributing to the recirculation phenomenon were behaving as clustered colonies. Fluid dynamics analysis indicated that particle recirculation within the partition column may be attributed to the combined effect of cluster formation and drag reduction. Both visiometric process analysis and particle coating experiments showed that smaller particles had greater propensity toward cluster formation than larger particles. The influence of cluster formation on coating performance and possible solutions to cluster formation were further discussed. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Physicochemical properties/descriptors governing the solubility and partitioning of chemicals in water-solvent-gas systems. Part 1. Partitioning between octanol and air.

PubMed

Raevsky, O A; Grigor'ev, V J; Raevskaja, O E; Schaper, K-J

2006-06-01

QSPR analyses of a data set containing experimental partition coefficients in the three systems octanol-water, water-gas, and octanol-gas for 98 chemicals have shown that it is possible to calculate any partition coefficient in the system 'gas phase/octanol/water' by three different approaches: (1) from experimental partition coefficients obtained in the corresponding two other subsystems. However, in many cases these data may not be available. Therefore, a solution may be approached (2), a traditional QSPR analysis based on e.g. HYBOT descriptors (hydrogen bond acceptor and donor factors, SigmaCa and SigmaCd, together with polarisability alpha, a steric bulk effect descriptor) and supplemented with substructural indicator variables. (3) A very promising approach which is a combination of the similarity concept and QSPR based on HYBOT descriptors. In this approach observed partition coefficients of structurally nearest neighbours of a compound-of-interest are used. In addition, contributions arising from differences in alpha, SigmaCa, and SigmaCd values between the compound-of-interest and its nearest neighbour(s), respectively, are considered. In this investigation highly significant relationships were obtained by approaches (1) and (3) for the octanol/gas phase partition coefficient (log Log).

Performance Comparison of a Set of Periodic and Non-Periodic Tridiagonal Solvers on SP2 and Paragon Parallel Computers

NASA Technical Reports Server (NTRS)

Sun, Xian-He; Moitra, Stuti

1996-01-01

Various tridiagonal solvers have been proposed in recent years for different parallel platforms. In this paper, the performance of three tridiagonal solvers, namely, the parallel partition LU algorithm, the parallel diagonal dominant algorithm, and the reduced diagonal dominant algorithm, is studied. These algorithms are designed for distributed-memory machines and are tested on an Intel Paragon and an IBM SP2 machines. Measured results are reported in terms of execution time and speedup. Analytical study are conducted for different communication topologies and for different tridiagonal systems. The measured results match the analytical results closely. In addition to address implementation issues, performance considerations such as problem sizes and models of speedup are also discussed.

High Pressure/Temperature Metal Silicate Partitioning of Tungsten

NASA Technical Reports Server (NTRS)

Shofner, G. A.; Danielson, L.; Righter, K.; Campbell, A. J.

2010-01-01

The behavior of chemical elements during metal/silicate segregation and their resulting distribution in Earth's mantle and core provide insight into core formation processes. Experimental determination of partition coefficients allows calculations of element distributions that can be compared to accepted values of element abundances in the silicate (mantle) and metallic (core) portions of the Earth. Tungsten (W) is a moderately siderophile element and thus preferentially partitions into metal versus silicate under many planetary conditions. The partitioning behavior has been shown to vary with temperature, silicate composition, oxygen fugacity, and pressure. Most of the previous work on W partitioning has been conducted at 1-bar conditions or at relatively low pressures, i.e. <10 GPa, and in two cases at or near 20 GPa. According to those data, the stronger influences on the distribution coefficient of W are temperature, composition, and oxygen fugacity with a relatively slight influence in pressure. Predictions based on extrapolation of existing data and parameterizations suggest an increased pressured dependence on metal/ silicate partitioning of W at higher pressures 5. However, the dependence on pressure is not as well constrained as T, fO2, and silicate composition. This poses a problem because proposed equilibration pressures for core formation range from 27 to 50 GPa, falling well outside the experimental range, therefore requiring exptrapolation of a parametereized model. Higher pressure data are needed to improve our understanding of W partitioning at these more extreme conditions.

Manual hierarchical clustering of regional geochemical data using a Bayesian finite mixture model

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David

2016-01-01

Interpretation of regional scale, multivariate geochemical data is aided by a statistical technique called “clustering.” We investigate a particular clustering procedure by applying it to geochemical data collected in the State of Colorado, United States of America. The clustering procedure partitions the field samples for the entire survey area into two clusters. The field samples in each cluster are partitioned again to create two subclusters, and so on. This manual procedure generates a hierarchy of clusters, and the different levels of the hierarchy show geochemical and geological processes occurring at different spatial scales. Although there are many different clustering methods, we use Bayesian finite mixture modeling with two probability distributions, which yields two clusters. The model parameters are estimated with Hamiltonian Monte Carlo sampling of the posterior probability density function, which usually has multiple modes. Each mode has its own set of model parameters; each set is checked to ensure that it is consistent both with the data and with independent geologic knowledge. The set of model parameters that is most consistent with the independent geologic knowledge is selected for detailed interpretation and partitioning of the field samples.

New Parallel Algorithms for Landscape Evolution Model

NASA Astrophysics Data System (ADS)

Jin, Y.; Zhang, H.; Shi, Y.

2017-12-01

Most landscape evolution models (LEM) developed in the last two decades solve the diffusion equation to simulate the transportation of surface sediments. This numerical approach is difficult to parallelize due to the computation of drainage area for each node, which needs huge amount of communication if run in parallel. In order to overcome this difficulty, we developed two parallel algorithms for LEM with a stream net. One algorithm handles the partition of grid with traditional methods and applies an efficient global reduction algorithm to do the computation of drainage areas and transport rates for the stream net; the other algorithm is based on a new partition algorithm, which partitions the nodes in catchments between processes first, and then partitions the cells according to the partition of nodes. Both methods focus on decreasing communication between processes and take the advantage of massive computing techniques, and numerical experiments show that they are both adequate to handle large scale problems with millions of cells. We implemented the two algorithms in our program based on the widely used finite element library deal.II, so that it can be easily coupled with ASPECT.

Evolving bipartite authentication graph partitions

DOE PAGES

Pope, Aaron Scott; Tauritz, Daniel Remy; Kent, Alexander D.

2017-01-16

As large scale enterprise computer networks become more ubiquitous, finding the appropriate balance between user convenience and user access control is an increasingly challenging proposition. Suboptimal partitioning of users’ access and available services contributes to the vulnerability of enterprise networks. Previous edge-cut partitioning methods unduly restrict users’ access to network resources. This paper introduces a novel method of network partitioning superior to the current state-of-the-art which minimizes user impact by providing alternate avenues for access that reduce vulnerability. Networks are modeled as bipartite authentication access graphs and a multi-objective evolutionary algorithm is used to simultaneously minimize the size of largemore » connected components while minimizing overall restrictions on network users. Lastly, results are presented on a real world data set that demonstrate the effectiveness of the introduced method compared to previous naive methods.« less

Platinum Partitioning at Low Oxygen Fugacity: Implications for Core Formation Processes

NASA Technical Reports Server (NTRS)

Medard, E.; Martin, A. M.; Righter, K.; Lanziroti, A.; Newville, M.

2016-01-01

Highly siderophile elements (HSE = Au, Re, and the Pt-group elements) are tracers of silicate / metal interactions during planetary processes. Since most core-formation models involve some state of equilibrium between liquid silicate and liquid metal, understanding the partioning of highly siderophile elements (HSE) between silicate and metallic melts is a key issue for models of core / mantle equilibria and for core formation scenarios. However, partitioning models for HSE are still inaccurate due to the lack of sufficient experimental constraints to describe the variations of partitioning with key variable like temperature, pressure, and oxygen fugacity. In this abstract, we describe a self-consistent set of experiments aimed at determining the valence of platinum, one of the HSE, in silicate melts. This is a key information required to parameterize the evolution of platinum partitioning with oxygen fugacity.

Evolving bipartite authentication graph partitions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pope, Aaron Scott; Tauritz, Daniel Remy; Kent, Alexander D.

As large scale enterprise computer networks become more ubiquitous, finding the appropriate balance between user convenience and user access control is an increasingly challenging proposition. Suboptimal partitioning of users’ access and available services contributes to the vulnerability of enterprise networks. Previous edge-cut partitioning methods unduly restrict users’ access to network resources. This paper introduces a novel method of network partitioning superior to the current state-of-the-art which minimizes user impact by providing alternate avenues for access that reduce vulnerability. Networks are modeled as bipartite authentication access graphs and a multi-objective evolutionary algorithm is used to simultaneously minimize the size of largemore » connected components while minimizing overall restrictions on network users. Lastly, results are presented on a real world data set that demonstrate the effectiveness of the introduced method compared to previous naive methods.« less

Soft sensor modeling based on variable partition ensemble method for nonlinear batch processes

NASA Astrophysics Data System (ADS)

Wang, Li; Chen, Xiangguang; Yang, Kai; Jin, Huaiping

2017-01-01

Batch processes are always characterized by nonlinear and system uncertain properties, therefore, the conventional single model may be ill-suited. A local learning strategy soft sensor based on variable partition ensemble method is developed for the quality prediction of nonlinear and non-Gaussian batch processes. A set of input variable sets are obtained by bootstrapping and PMI criterion. Then, multiple local GPR models are developed based on each local input variable set. When a new test data is coming, the posterior probability of each best performance local model is estimated based on Bayesian inference and used to combine these local GPR models to get the final prediction result. The proposed soft sensor is demonstrated by applying to an industrial fed-batch chlortetracycline fermentation process.

Quantum annealing for the number-partitioning problem using a tunable spin glass of ions

PubMed Central

Graß, Tobias; Raventós, David; Juliá-Díaz, Bruno; Gogolin, Christian; Lewenstein, Maciej

2016-01-01

Exploiting quantum properties to outperform classical ways of information processing is an outstanding goal of modern physics. A promising route is quantum simulation, which aims at implementing relevant and computationally hard problems in controllable quantum systems. Here we demonstrate that in a trapped ion setup, with present day technology, it is possible to realize a spin model of the Mattis-type that exhibits spin glass phases. Our method produces the glassy behaviour without the need for any disorder potential, just by controlling the detuning of the spin-phonon coupling. Applying a transverse field, the system can be used to benchmark quantum annealing strategies which aim at reaching the ground state of the spin glass starting from the paramagnetic phase. In the vicinity of a phonon resonance, the problem maps onto number partitioning, and instances which are difficult to address classically can be implemented. PMID:27230802

High-performance parallel analysis of coupled problems for aircraft propulsion

NASA Technical Reports Server (NTRS)

Felippa, C. A.; Farhat, C.; Lanteri, S.; Maman, N.; Piperno, S.; Gumaste, U.

1994-01-01

This research program deals with the application of high-performance computing methods for the analysis of complete jet engines. We have entitled this program by applying the two dimensional parallel aeroelastic codes to the interior gas flow problem of a bypass jet engine. The fluid mesh generation, domain decomposition, and solution capabilities were successfully tested. We then focused attention on methodology for the partitioned analysis of the interaction of the gas flow with a flexible structure and with the fluid mesh motion that results from these structural displacements. This is treated by a new arbitrary Lagrangian-Eulerian (ALE) technique that models the fluid mesh motion as that of a fictitious mass-spring network. New partitioned analysis procedures to treat this coupled three-component problem are developed. These procedures involved delayed corrections and subcycling. Preliminary results on the stability, accuracy, and MPP computational efficiency are reported.

Calculation of excitation energies from the CC2 linear response theory using Cholesky decomposition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Baudin, Pablo, E-mail: baudin.pablo@gmail.com; qLEAP – Center for Theoretical Chemistry, Department of Chemistry, Aarhus University, Langelandsgade 140, DK-8000 Aarhus C; Marín, José Sánchez

2014-03-14

A new implementation of the approximate coupled cluster singles and doubles CC2 linear response model is reported. It employs a Cholesky decomposition of the two-electron integrals that significantly reduces the computational cost and the storage requirements of the method compared to standard implementations. Our algorithm also exploits a partitioning form of the CC2 equations which reduces the dimension of the problem and avoids the storage of doubles amplitudes. We present calculation of excitation energies of benzene using a hierarchy of basis sets and compare the results with conventional CC2 calculations. The reduction of the scaling is evaluated as well asmore » the effect of the Cholesky decomposition parameter on the quality of the results. The new algorithm is used to perform an extrapolation to complete basis set investigation on the spectroscopically interesting benzylallene conformers. A set of calculations on medium-sized molecules is carried out to check the dependence of the accuracy of the results on the decomposition thresholds. Moreover, CC2 singlet excitation energies of the free base porphin are also presented.« less

Partitioning behavior of aromatic components in jet fuel into diverse membrane-coated fibers.

PubMed

Baynes, Ronald E; Xia, Xin-Rui; Barlow, Beth M; Riviere, Jim E

2007-11-01

Jet fuel components are known to partition into skin and produce occupational irritant contact dermatitis (OICD) and potentially adverse systemic effects. The purpose of this study was to determine how jet fuel components partition (1) from solvent mixtures into diverse membrane-coated fibers (MCFs) and (2) from biological media into MCFs to predict tissue distribution. Three diverse MCFs, polydimethylsiloxane (PDMS, lipophilic), polyacrylate (PA, polarizable), and carbowax (CAR, polar), were selected to simulate the physicochemical properties of skin in vivo. Following an appropriate equilibrium time between the MCF and dosing solutions, the MCF was injected directly into a gas chromatograph/mass spectrometer (GC-MS) to quantify the amount that partitioned into the membrane. Three vehicles (water, 50% ethanol-water, and albumin-containing media solution) were studied for selected jet fuel components. The more hydrophobic the component, the greater was the partitioning into the membranes across all MCF types, especially from water. The presence of ethanol as a surrogate solvent resulted in significantly reduced partitioning into the MCFs with discernible differences across the three fibers based on their chemistries. The presence of a plasma substitute (media) also reduced partitioning into the MCF, with the CAR MCF system being better correlated to the predicted partitioning of aromatic components into skin. This study demonstrated that a single or multiple set of MCF fibers may be used as a surrogate for octanol/water systems and skin to assess partitioning behavior of nine aromatic components frequently formulated with jet fuels. These diverse inert fibers were able to assess solute partitioning from a blood substitute such as media into a membrane possessing physicochemical properties similar to human skin. This information may be incorporated into physiologically based pharmacokinetic (PBPK) models to provide a more accurate assessment of tissue dosimetry of related toxicants.

Rational design of polymer-based absorbents: application to the fermentation inhibitor furfural.

PubMed

Nwaneshiudu, Ikechukwu C; Schwartz, Daniel T

2015-01-01

Reducing the amount of water-soluble fermentation inhibitors like furfural is critical for downstream bio-processing steps to biofuels. A theoretical approach for tailoring absorption polymers to reduce these pretreatment contaminants would be useful for optimal bioprocess design. Experiments were performed to measure aqueous furfural partitioning into polymer resins of 5 bisphenol A diglycidyl ether (epoxy) and polydimethylsiloxane (PDMS). Experimentally measured partitioning of furfural between water and PDMS, the more hydrophobic polymer, showed poor performance, with the logarithm of PDMS-to-water partition coefficient falling between -0.62 and -0.24 (95% confidence). In contrast, the fast setting epoxy was found to effectively partition furfural with the logarithm of the epoxy-to-water partition coefficient falling between 0.41 and 0.81 (95% confidence). Flory-Huggins theory is used to predict the partitioning of furfural into diverse polymer absorbents and is useful for predicting these results. We show that Flory-Huggins theory can be adapted to guide the selection of polymer adsorbents for the separation of low molecular weight organic species from aqueous solutions. This work lays the groundwork for the general design of polymers for the separation of a wide range of inhibitory compounds in biomass pretreatment streams.

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

NASA Technical Reports Server (NTRS)

Koch, Patrick N.

1997-01-01

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Stochastic control approaches for sensor management in search and exploitation

NASA Astrophysics Data System (ADS)

Hitchings, Darin Chester

Recent improvements in the capabilities of autonomous vehicles have motivated their increased use in such applications as defense, homeland security, environmental monitoring, and surveillance. To enhance performance in these applications, new algorithms are required to control teams of robots autonomously and through limited interactions with human operators. In this dissertation we develop new algorithms for control of robots performing information-seeking missions in unknown environments. These missions require robots to control their sensors in order to discover the presence of objects, keep track of the objects, and learn what these objects are, given a fixed sensing budget. Initially, we investigate control of multiple sensors, with a finite set of sensing options and finite-valued measurements, to locate and classify objects given a limited resource budget. The control problem is formulated as a Partially Observed Markov Decision Problem (POMDP), but its exact solution requires excessive computation. Under the assumption that sensor error statistics are independent and time-invariant, we develop a class of algorithms using Lagrangian Relaxation techniques to obtain optimal mixed strategies using performance bounds developed in previous research. We investigate alternative Receding Horizon (RH) controllers to convert the mixed strategies to feasible adaptive-sensing strategies and evaluate the relative performance of these controllers in simulation. The resulting controllers provide superior performance to alternative algorithms proposed in the literature and obtain solutions to large-scale POMDP problems several orders of magnitude faster than optimal Dynamic Programming (DP) approaches with comparable performance quality. We extend our results for finite action, finite measurement sensor control to scenarios with moving objects. We use Hidden Markov Models (HMMs) for the evolution of objects, according to the dynamics of a birth-death process. We develop a new lower bound on the performance of adaptive controllers in these scenarios, develop algorithms for computing solutions to this lower bound, and use these algorithms as part of a RH controller for sensor allocation in the presence of moving objects We also consider an adaptive Search problem where sensing actions are continuous and the underlying measurement space is also continuous. We extend our previous hierarchical decomposition approach based on performance bounds to this problem and develop novel implementations of Stochastic Dynamic Programming (SDP) techniques to solve this problem. Our algorithms are nearly two orders of magnitude faster than previously proposed approaches and yield solutions of comparable quality. For supervisory control, we discuss how human operators can work with and augment robotic teams performing these tasks. Our focus is on how tasks are partitioned among teams of robots and how a human operator can make intelligent decisions for task partitioning. We explore these questions through the design of a game that involves robot automata controlled by our algorithms and a human supervisor that partitions tasks based on different levels of support information. This game can be used with human subject experiments to explore the effect of information on quality of supervisory control.

Linear scaling computation of the Fock matrix. VI. Data parallel computation of the exchange-correlation matrix

NASA Astrophysics Data System (ADS)

Gan, Chee Kwan; Challacombe, Matt

2003-05-01

Recently, early onset linear scaling computation of the exchange-correlation matrix has been achieved using hierarchical cubature [J. Chem. Phys. 113, 10037 (2000)]. Hierarchical cubature differs from other methods in that the integration grid is adaptive and purely Cartesian, which allows for a straightforward domain decomposition in parallel computations; the volume enclosing the entire grid may be simply divided into a number of nonoverlapping boxes. In our data parallel approach, each box requires only a fraction of the total density to perform the necessary numerical integrations due to the finite extent of Gaussian-orbital basis sets. This inherent data locality may be exploited to reduce communications between processors as well as to avoid memory and copy overheads associated with data replication. Although the hierarchical cubature grid is Cartesian, naive boxing leads to irregular work loads due to strong spatial variations of the grid and the electron density. In this paper we describe equal time partitioning, which employs time measurement of the smallest sub-volumes (corresponding to the primitive cubature rule) to load balance grid-work for the next self-consistent-field iteration. After start-up from a heuristic center of mass partitioning, equal time partitioning exploits smooth variation of the density and grid between iterations to achieve load balance. With the 3-21G basis set and a medium quality grid, equal time partitioning applied to taxol (62 heavy atoms) attained a speedup of 61 out of 64 processors, while for a 110 molecule water cluster at standard density it achieved a speedup of 113 out of 128. The efficiency of equal time partitioning applied to hierarchical cubature improves as the grid work per processor increases. With a fine grid and the 6-311G(df,p) basis set, calculations on the 26 atom molecule α-pinene achieved a parallel efficiency better than 99% with 64 processors. For more coarse grained calculations, superlinear speedups are found to result from reduced computational complexity associated with data parallelism.

This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms--theory and practice.

PubMed

Harmany, Zachary T; Marcia, Roummel F; Willett, Rebecca M

2012-03-01

Observations in many applications consist of counts of discrete events, such as photons hitting a detector, which cannot be effectively modeled using an additive bounded or Gaussian noise model, and instead require a Poisson noise model. As a result, accurate reconstruction of a spatially or temporally distributed phenomenon (f*) from Poisson data (y) cannot be effectively accomplished by minimizing a conventional penalized least-squares objective function. The problem addressed in this paper is the estimation of f* from y in an inverse problem setting, where the number of unknowns may potentially be larger than the number of observations and f* admits sparse approximation. The optimization formulation considered in this paper uses a penalized negative Poisson log-likelihood objective function with nonnegativity constraints (since Poisson intensities are naturally nonnegative). In particular, the proposed approach incorporates key ideas of using separable quadratic approximations to the objective function at each iteration and penalization terms related to l1 norms of coefficient vectors, total variation seminorms, and partition-based multiscale estimation methods.

Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL): adapting the Partial Phylogenetic Profiling algorithm to scan sequences for signatures that predict protein function

PubMed Central

2010-01-01

Background Comparative genomics methods such as phylogenetic profiling can mine powerful inferences from inherently noisy biological data sets. We introduce Sites Inferred by Metabolic Background Assertion Labeling (SIMBAL), a method that applies the Partial Phylogenetic Profiling (PPP) approach locally within a protein sequence to discover short sequence signatures associated with functional sites. The approach is based on the basic scoring mechanism employed by PPP, namely the use of binomial distribution statistics to optimize sequence similarity cutoffs during searches of partitioned training sets. Results Here we illustrate and validate the ability of the SIMBAL method to find functionally relevant short sequence signatures by application to two well-characterized protein families. In the first example, we partitioned a family of ABC permeases using a metabolic background property (urea utilization). Thus, the TRUE set for this family comprised members whose genome of origin encoded a urea utilization system. By moving a sliding window across the sequence of a permease, and searching each subsequence in turn against the full set of partitioned proteins, the method found which local sequence signatures best correlated with the urea utilization trait. Mapping of SIMBAL "hot spots" onto crystal structures of homologous permeases reveals that the significant sites are gating determinants on the cytosolic face rather than, say, docking sites for the substrate-binding protein on the extracellular face. In the second example, we partitioned a protein methyltransferase family using gene proximity as a criterion. In this case, the TRUE set comprised those methyltransferases encoded near the gene for the substrate RF-1. SIMBAL identifies sequence regions that map onto the substrate-binding interface while ignoring regions involved in the methyltransferase reaction mechanism in general. Neither method for training set construction requires any prior experimental characterization. Conclusions SIMBAL shows that, in functionally divergent protein families, selected short sequences often significantly outperform their full-length parent sequence for making functional predictions by sequence similarity, suggesting avenues for improved functional classifiers. When combined with structural data, SIMBAL affords the ability to localize and model functional sites. PMID:20102603

An in situ approach to study trace element partitioning in the laser heated diamond anvil cell

DOE Office of Scientific and Technical Information (OSTI.GOV)

Petitgirard, S.; Mezouar, M.; Borchert, M.

2012-01-15

Data on partitioning behavior of elements between different phases at in situ conditions are crucial for the understanding of element mobility especially for geochemical studies. Here, we present results of in situ partitioning of trace elements (Zr, Pd, and Ru) between silicate and iron melts, up to 50 GPa and 4200 K, using a modified laser heated diamond anvil cell (DAC). This new experimental set up allows simultaneous collection of x-ray fluorescence (XRF) and x-ray diffraction (XRD) data as a function of time using the high pressure beamline ID27 (ESRF, France). The technique enables the simultaneous detection of sample meltingmore » based to the appearance of diffuse scattering in the XRD pattern, characteristic of the structure factor of liquids, and measurements of elemental partitioning of the sample using XRF, before, during and after laser heating in the DAC. We were able to detect elements concentrations as low as a few ppm level (2-5 ppm) on standard solutions. In situ measurements are complimented by mapping of the chemical partitions of the trace elements after laser heating on the quenched samples to constrain the partitioning data. Our first results indicate a strong partitioning of Pd and Ru into the metallic phase, while Zr remains clearly incompatible with iron. This novel approach extends the pressure and temperature range of partitioning experiments derived from quenched samples from the large volume presses and could bring new insight to the early history of Earth.« less

A Brief Measure of Children's Behavior Problems: The Behavior Rating Index for Children.

ERIC Educational Resources Information Center

Stiffman, Arlene R.; And Others

1984-01-01

Describes the development of the Behavior Rating Index for Children (BRIC), a 13-item summated category partition scale that provides a prothetic measure of children's behavior problems. Evaluation of the BRIC with 600 referred and nonreferred children suggested adequate reliability and validity. (JAC)

Analysis, preliminary design and simulation systems for control-structure interaction problems

NASA Technical Reports Server (NTRS)

Park, K. C.; Alvin, Kenneth F.

1991-01-01

Software aspects of control-structure interaction (CSI) analysis are discussed. The following subject areas are covered: (1) implementation of a partitioned algorithm for simulation of large CSI problems; (2) second-order discrete Kalman filtering equations for CSI simulations; and (3) parallel computations and control of adaptive structures.

On models of the genetic code generated by binary dichotomic algorithms.

PubMed

Gumbel, Markus; Fimmel, Elena; Danielli, Alberto; Strüngmann, Lutz

2015-02-01

In this paper we introduce the concept of a BDA-generated model of the genetic code which is based on binary dichotomic algorithms (BDAs). A BDA-generated model is based on binary dichotomic algorithms (BDAs). Such a BDA partitions the set of 64 codons into two disjoint classes of size 32 each and provides a generalization of known partitions like the Rumer dichotomy. We investigate what partitions can be generated when a set of different BDAs is applied sequentially to the set of codons. The search revealed that these models are able to generate code tables with very different numbers of classes ranging from 2 to 64. We have analyzed whether there are models that map the codons to their amino acids. A perfect matching is not possible. However, we present models that describe the standard genetic code with only few errors. There are also models that map all 64 codons uniquely to 64 classes showing that BDAs can be used to identify codons precisely. This could serve as a basis for further mathematical analysis using coding theory, for example. The hypothesis that BDAs might reflect a molecular mechanism taking place in the decoding center of the ribosome is discussed. The scan demonstrated that binary dichotomic partitions are able to model different aspects of the genetic code very well. The search was performed with our tool Beady-A. This software is freely available at http://mi.informatik.hs-mannheim.de/beady-a. It requires a JVM version 6 or higher. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Conceptual structure and the procedural affordances of rational numbers: relational reasoning with fractions and decimals.

PubMed

DeWolf, Melissa; Bassok, Miriam; Holyoak, Keith J

2015-02-01

The standard number system includes several distinct types of notations, which differ conceptually and afford different procedures. Among notations for rational numbers, the bipartite format of fractions (a/b) enables them to represent 2-dimensional relations between sets of discrete (i.e., countable) elements (e.g., red marbles/all marbles). In contrast, the format of decimals is inherently 1-dimensional, expressing a continuous-valued magnitude (i.e., proportion) but not a 2-dimensional relation between sets of countable elements. Experiment 1 showed that college students indeed view these 2-number notations as conceptually distinct. In a task that did not involve mathematical calculations, participants showed a strong preference to represent partitioned displays of discrete objects with fractions and partitioned displays of continuous masses with decimals. Experiment 2 provided evidence that people are better able to identify and evaluate ratio relationships using fractions than decimals, especially for discrete (or discretized) quantities. Experiments 3 and 4 found a similar pattern of performance for a more complex analogical reasoning task. When solving relational reasoning problems based on discrete or discretized quantities, fractions yielded greater accuracy than decimals; in contrast, when quantities were continuous, accuracy was lower for both symbolic notations. Whereas previous research has established that decimals are more effective than fractions in supporting magnitude comparisons, the present study reveals that fractions are relatively advantageous in supporting relational reasoning with discrete (or discretized) concepts. These findings provide an explanation for the effectiveness of natural frequency formats in supporting some types of reasoning, and have implications for teaching of rational numbers.

Predicate Oriented Pattern Analysis for Biomedical Knowledge Discovery

PubMed Central

Shen, Feichen; Liu, Hongfang; Sohn, Sunghwan; Larson, David W.; Lee, Yugyung

2017-01-01

In the current biomedical data movement, numerous efforts have been made to convert and normalize a large number of traditional structured and unstructured data (e.g., EHRs, reports) to semi-structured data (e.g., RDF, OWL). With the increasing number of semi-structured data coming into the biomedical community, data integration and knowledge discovery from heterogeneous domains become important research problem. In the application level, detection of related concepts among medical ontologies is an important goal of life science research. It is more crucial to figure out how different concepts are related within a single ontology or across multiple ontologies by analysing predicates in different knowledge bases. However, the world today is one of information explosion, and it is extremely difficult for biomedical researchers to find existing or potential predicates to perform linking among cross domain concepts without any support from schema pattern analysis. Therefore, there is a need for a mechanism to do predicate oriented pattern analysis to partition heterogeneous ontologies into closer small topics and do query generation to discover cross domain knowledge from each topic. In this paper, we present such a model that predicates oriented pattern analysis based on their close relationship and generates a similarity matrix. Based on this similarity matrix, we apply an innovated unsupervised learning algorithm to partition large data sets into smaller and closer topics and generate meaningful queries to fully discover knowledge over a set of interlinked data sources. We have implemented a prototype system named BmQGen and evaluate the proposed model with colorectal surgical cohort from the Mayo Clinic. PMID:28983419

Multi-Objective Community Detection Based on Memetic Algorithm

PubMed Central

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels. PMID:25932646

Multi-objective community detection based on memetic algorithm.

PubMed

Wu, Peng; Pan, Li

2015-01-01

Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

Efficient O(N) integration for all-electron electronic structure calculation using numeric basis functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Havu, V.; Fritz Haber Institute of the Max Planck Society, Berlin; Blum, V.

2009-12-01

We consider the problem of developing O(N) scaling grid-based operations needed in many central operations when performing electronic structure calculations with numeric atom-centered orbitals as basis functions. We outline the overall formulation of localized algorithms, and specifically the creation of localized grid batches. The choice of the grid partitioning scheme plays an important role in the performance and memory consumption of the grid-based operations. Three different top-down partitioning methods are investigated, and compared with formally more rigorous yet much more expensive bottom-up algorithms. We show that a conceptually simple top-down grid partitioning scheme achieves essentially the same efficiency as themore » more rigorous bottom-up approaches.« less

On distributed wavefront reconstruction for large-scale adaptive optics systems.

PubMed

de Visser, Cornelis C; Brunner, Elisabeth; Verhaegen, Michel

2016-05-01

The distributed-spline-based aberration reconstruction (D-SABRE) method is proposed for distributed wavefront reconstruction with applications to large-scale adaptive optics systems. D-SABRE decomposes the wavefront sensor domain into any number of partitions and solves a local wavefront reconstruction problem on each partition using multivariate splines. D-SABRE accuracy is within 1% of a global approach with a speedup that scales quadratically with the number of partitions. The D-SABRE is compared to the distributed cumulative reconstruction (CuRe-D) method in open-loop and closed-loop simulations using the YAO adaptive optics simulation tool. D-SABRE accuracy exceeds CuRe-D for low levels of decomposition, and D-SABRE proved to be more robust to variations in the loop gain.

Asymptotic Normality Through Factorial Cumulants and Partition Identities

PubMed Central

Bobecka, Konstancja; Hitczenko, Paweł; López-Blázquez, Fernando; Rempała, Grzegorz; Wesołowski, Jacek

2013-01-01

In the paper we develop an approach to asymptotic normality through factorial cumulants. Factorial cumulants arise in the same manner from factorial moments as do (ordinary) cumulants from (ordinary) moments. Another tool we exploit is a new identity for ‘moments’ of partitions of numbers. The general limiting result is then used to (re-)derive asymptotic normality for several models including classical discrete distributions, occupancy problems in some generalized allocation schemes and two models related to negative multinomial distribution. PMID:24591773

On k-ary n-cubes: Theory and applications

NASA Technical Reports Server (NTRS)

Mao, Weizhen; Nicol, David M.

1994-01-01

Many parallel processing networks can be viewed as graphs called k-ary n-cubes, whose special cases include rings, hypercubes and toruses. In this paper, combinatorial properties of k-ary n-cubes are explored. In particular, the problem of characterizing the subgraph of a given number of nodes with the maximum edge count is studied. These theoretical results are then used to compute a lower bounding function in branch-and-bound partitioning algorithms and to establish the optimality of some irregular partitions.

Three-Dimensional High-Order Spectral Finite Volume Method for Unstructured Grids

NASA Technical Reports Server (NTRS)

Liu, Yen; Vinokur, Marcel; Wang, Z. J.; Kwak, Dochan (Technical Monitor)

2002-01-01

Many areas require a very high-order accurate numerical solution of conservation laws for complex shapes. This paper deals with the extension to three dimensions of the Spectral Finite Volume (SV) method for unstructured grids, which was developed to solve such problems. We first summarize the limitations of traditional methods such as finite-difference, and finite-volume for both structured and unstructured grids. We then describe the basic formulation of the spectral finite volume method. What distinguishes the SV method from conventional high-order finite-volume methods for unstructured triangular or tetrahedral grids is the data reconstruction. Instead of using a large stencil of neighboring cells to perform a high-order reconstruction, the stencil is constructed by partitioning each grid cell, called a spectral volume (SV), into 'structured' sub-cells, called control volumes (CVs). One can show that if all the SV cells are partitioned into polygonal or polyhedral CV sub-cells in a geometrically similar manner, the reconstructions for all the SVs become universal, irrespective of their shapes, sizes, orientations, or locations. It follows that the reconstruction is reduced to a weighted sum of unknowns involving just a few simple adds and multiplies, and those weights are universal and can be pre-determined once for all. The method is thus very efficient, accurate, and yet geometrically flexible. The most critical part of the SV method is the partitioning of the SV into CVs. In this paper we present the partitioning of a tetrahedral SV into polyhedral CVs with one free parameter for polynomial reconstructions up to degree of precision five. (Note that the order of accuracy of the method is one order higher than the reconstruction degree of precision.) The free parameter will be determined by minimizing the Lebesgue constant of the reconstruction matrix or similar criteria to obtain optimized partitions. The details of an efficient, parallelizable code to solve three-dimensional problems for any order of accuracy are then presented. Important aspects of the data structure are discussed. Comparisons with the Discontinuous Galerkin (DG) method are made. Numerical examples for wave propagation problems are presented.

Partitioning of K, U, and TH between sulfide and silicate liquids: Implications for radioactive heating of planetary cores

NASA Astrophysics Data System (ADS)

Murrell, M. T.; Burnett, D. S.

1986-07-01

The possibility of heating of planetary cores by K radioactivity has been extensively discussed, as well as the possibility that K partitioning into the terrestrial core is the reason for the difference between the terrestrial and chondritic K/U. We had previously suggested that U and Th partitioning into FeFeS liquids was more important than K. Laboratory FeFeS liquid, silicate liquid partition coefficient measurements (D) for K, U, and Th were made to test this suggestion. For a basaltic liquid at 1450°C and 1.5 GPa, DU is 0.013 and DK is 0.0026; thus U partitioning into FeFeS liquids is 5 times greater than K partitioning under these conditions. There are problems with 1-atm experiments in that they do not appear to equilibrate or reverse. However, measurable U and Th partitioning into sulfide was nearly always observed, but K partitioning was normally not observed (DK <~ 10-4). A typical value for DU from a granitic silicate liquid at one atmosphere, 1150°C, and low f02 is about 0.02; DTh is similar. At low f02 and higher temperature, experiments with basaltic liquids produce strong Ca and U partitioning into the sulfide liquid with DU > 1. DTh is less strongly affected. Because of the consistently low DK/DU, pressure effects near the core-mantle boundary would need to increase DK by factors of ~103 with much smaller increases in DU in order to have the terrestrial K and U abundances at chondritic levels. In addition, if radioactive heating is important for planetary cores, U and Th will be more important than K unless the lower mantle has K/U greater than 10 times chondritic or large changes in partition coefficients with conditions reverse the relative importance of K versus U and Th from our measurements.

STACCATO: a novel solution to supernova photometric classification with biased training sets

NASA Astrophysics Data System (ADS)

Revsbech, E. A.; Trotta, R.; van Dyk, D. A.

2018-01-01

We present a new solution to the problem of classifying Type Ia supernovae from their light curves alone given a spectroscopically confirmed but biased training set, circumventing the need to obtain an observationally expensive unbiased training set. We use Gaussian processes (GPs) to model the supernovae's (SN's) light curves, and demonstrate that the choice of covariance function has only a small influence on the GPs ability to accurately classify SNe. We extend and improve the approach of Richards et al. - a diffusion map combined with a random forest classifier - to deal specifically with the case of biased training sets. We propose a novel method called Synthetically Augmented Light Curve Classification (STACCATO) that synthetically augments a biased training set by generating additional training data from the fitted GPs. Key to the success of the method is the partitioning of the observations into subgroups based on their propensity score of being included in the training set. Using simulated light curve data, we show that STACCATO increases performance, as measured by the area under the Receiver Operating Characteristic curve (AUC), from 0.93 to 0.96, close to the AUC of 0.977 obtained using the 'gold standard' of an unbiased training set and significantly improving on the previous best result of 0.88. STACCATO also increases the true positive rate for SNIa classification by up to a factor of 50 for high-redshift/low-brightness SNe.

Constant-Time Pattern Matching For Real-Time Production Systems

NASA Astrophysics Data System (ADS)

Parson, Dale E.; Blank, Glenn D.

1989-03-01

Many intelligent systems must respond to sensory data or critical environmental conditions in fixed, predictable time. Rule-based systems, including those based on the efficient Rete matching algorithm, cannot guarantee this result. Improvement in execution-time efficiency is not all that is needed here; it is important to ensure constant, 0(1) time limits for portions of the matching process. Our approach is inspired by two observations about human performance. First, cognitive psychologists distinguish between automatic and controlled processing. Analogously, we partition the matching process across two networks. The first is the automatic partition; it is characterized by predictable 0(1) time and space complexity, lack of persistent memory, and is reactive in nature. The second is the controlled partition; it includes the search-based goal-driven and data-driven processing typical of most production system programming. The former is responsible for recognition and response to critical environmental conditions. The latter is responsible for the more flexible problem-solving behaviors consistent with the notion of intelligence. Support for learning and refining the automatic partition can be placed in the controlled partition. Our second observation is that people are able to attend to more critical stimuli or requirements selectively. Our match algorithm uses priorities to focus matching. It compares priority of information during matching, rather than deferring this comparison until conflict resolution. Messages from the automatic partition are able to interrupt the controlled partition, enhancing system responsiveness. Our algorithm has numerous applications for systems that must exhibit time-constrained behavior.

Partition-free approach to open quantum systems in harmonic environments: An exact stochastic Liouville equation

NASA Astrophysics Data System (ADS)

McCaul, G. M. G.; Lorenz, C. D.; Kantorovich, L.

2017-03-01

We present a partition-free approach to the evolution of density matrices for open quantum systems coupled to a harmonic environment. The influence functional formalism combined with a two-time Hubbard-Stratonovich transformation allows us to derive a set of exact differential equations for the reduced density matrix of an open system, termed the extended stochastic Liouville-von Neumann equation. Our approach generalizes previous work based on Caldeira-Leggett models and a partitioned initial density matrix. This provides a simple, yet exact, closed-form description for the evolution of open systems from equilibriated initial conditions. The applicability of this model and the potential for numerical implementations are also discussed.

Lake Michigan Diversion Accounting land cover change estimation by use of the National Land Cover Dataset and raingage network partitioning analysis

USGS Publications Warehouse

Sharpe, Jennifer B.; Soong, David T.

2015-01-01

This study used the National Land Cover Dataset (NLCD) and developed an automated process for determining the area of the three land cover types, thereby allowing faster updating of future models, and for evaluating land cover changes by use of historical NLCD datasets. The study also carried out a raingage partitioning analysis so that the segmentation of land cover and rainfall in each modeled unit is directly applicable to the HSPF modeling. Historical and existing impervious, grass, and forest land acreages partitioned by percentages covered by two sets of raingages for the Lake Michigan diversion SCAs, gaged basins, and ungaged basins are presented.

Structural partitioning of complex structures in the medium-frequency range. An application to an automotive vehicle

NASA Astrophysics Data System (ADS)

Kassem, M.; Soize, C.; Gagliardini, L.

2011-02-01

In a recent work [ Journal of Sound and Vibration 323 (2009) 849-863] the authors presented an energy-density field approach for the vibroacoustic analysis of complex structures in the low and medium frequency ranges. In this approach, a local vibroacoustic energy model as well as a simplification of this model were constructed. In this paper, firstly an extension of the previous theory is performed in order to include the case of general input forces and secondly, a structural partitioning methodology is presented along with a set of tools used for the construction of a partitioning. Finally, an application is presented for an automotive vehicle.

Adaptively loaded IM/DD optical OFDM based on set-partitioned QAM formats.

PubMed

Zhao, Jian; Chen, Lian-Kuan

2017-04-17

We investigate the constellation design and symbol error rate (SER) of set-partitioned (SP) quadrature amplitude modulation (QAM) formats. Based on the SER analysis, we derive the adaptive bit and power loading algorithm for SP QAM based intensity-modulation direct-detection (IM/DD) orthogonal frequency division multiplexing (OFDM). We experimentally show that the proposed system significantly outperforms the conventional adaptively-loaded IM/DD OFDM and can increase the data rate from 36 Gbit/s to 42 Gbit/s in the presence of severe dispersion-induced spectral nulls after 40-km single-mode fiber. It is also shown that the adaptive algorithm greatly enhances the tolerance to fiber nonlinearity and allows for more power budget.

Joint image encryption and compression scheme based on IWT and SPIHT

NASA Astrophysics Data System (ADS)

Zhang, Miao; Tong, Xiaojun

2017-03-01

A joint lossless image encryption and compression scheme based on integer wavelet transform (IWT) and set partitioning in hierarchical trees (SPIHT) is proposed to achieve lossless image encryption and compression simultaneously. Making use of the properties of IWT and SPIHT, encryption and compression are combined. Moreover, the proposed secure set partitioning in hierarchical trees (SSPIHT) via the addition of encryption in the SPIHT coding process has no effect on compression performance. A hyper-chaotic system, nonlinear inverse operation, Secure Hash Algorithm-256(SHA-256), and plaintext-based keystream are all used to enhance the security. The test results indicate that the proposed methods have high security and good lossless compression performance.

Summer-winter concentrations and gas-particle partitioning of short chain chlorinated paraffins in the atmosphere of an urban setting.

PubMed

Wang, Thanh; Han, Shanlong; Yuan, Bo; Zeng, Lixi; Li, Yingming; Wang, Yawei; Jiang, Guibin

2012-12-01

Short chain chlorinated paraffins (SCCPs) are semi-volatile chemicals that are considered persistent in the environment, potential toxic and subject to long-range transport. This study investigates the concentrations and gas-particle partitioning of SCCPs at an urban site in Beijing during summer and wintertime. The total atmospheric SCCP levels ranged 1.9-33.0 ng/m(3) during wintertime. Significantly higher levels were found during the summer (range 112-332 ng/m(3)). The average fraction of total SCCPs in the particle phase (ϕ) was 0.67 during wintertime but decreased significantly during the summer (ϕ = 0.06). The ten and eleven carbon chain homologues with five to eight chlorine atoms were the predominant SCCP formula groups in air. Significant linear correlations were found between the gas-particle partition coefficients and the predicted subcooled vapor pressures and octanol-air partition coefficients. The gas-particle partitioning of SCCPs was further investigated and compared with both the Junge-Pankow adsorption and K(oa)-based absorption models. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

NASA Astrophysics Data System (ADS)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach

NASA Astrophysics Data System (ADS)

Fienen, M.; Hunt, R.; Krabbenhoft, D.; Clemo, T.

2009-08-01

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained.

Obtaining parsimonious hydraulic conductivity fields using head and transport observations: A Bayesian geostatistical parameter estimation approach

USGS Publications Warehouse

Fienen, M.; Hunt, R.; Krabbenhoft, D.; Clemo, T.

2009-01-01

Flow path delineation is a valuable tool for interpreting the subsurface hydrogeochemical environment. Different types of data, such as groundwater flow and transport, inform different aspects of hydrogeologic parameter values (hydraulic conductivity in this case) which, in turn, determine flow paths. This work combines flow and transport information to estimate a unified set of hydrogeologic parameters using the Bayesian geostatistical inverse approach. Parameter flexibility is allowed by using a highly parameterized approach with the level of complexity informed by the data. Despite the effort to adhere to the ideal of minimal a priori structure imposed on the problem, extreme contrasts in parameters can result in the need to censor correlation across hydrostratigraphic bounding surfaces. These partitions segregate parameters into facies associations. With an iterative approach in which partitions are based on inspection of initial estimates, flow path interpretation is progressively refined through the inclusion of more types of data. Head observations, stable oxygen isotopes (18O/16O ratios), and tritium are all used to progressively refine flow path delineation on an isthmus between two lakes in the Trout Lake watershed, northern Wisconsin, United States. Despite allowing significant parameter freedom by estimating many distributed parameter values, a smooth field is obtained.

Staggered solution procedures for multibody dynamics simulation

NASA Technical Reports Server (NTRS)

Park, K. C.; Chiou, J. C.; Downer, J. D.

1990-01-01

The numerical solution procedure for multibody dynamics (MBD) systems is termed a staggered MBD solution procedure that solves the generalized coordinates in a separate module from that for the constraint force. This requires a reformulation of the constraint conditions so that the constraint forces can also be integrated in time. A major advantage of such a partitioned solution procedure is that additional analysis capabilities such as active controller and design optimization modules can be easily interfaced without embedding them into a monolithic program. After introducing the basic equations of motion for MBD system in the second section, Section 3 briefly reviews some constraint handling techniques and introduces the staggered stabilized technique for the solution of the constraint forces as independent variables. The numerical direct time integration of the equations of motion is described in Section 4. As accurate damping treatment is important for the dynamics of space structures, we have employed the central difference method and the mid-point form of the trapezoidal rule since they engender no numerical damping. This is in contrast to the current practice in dynamic simulations of ground vehicles by employing a set of backward difference formulas. First, the equations of motion are partitioned according to the translational and the rotational coordinates. This sets the stage for an efficient treatment of the rotational motions via the singularity-free Euler parameters. The resulting partitioned equations of motion are then integrated via a two-stage explicit stabilized algorithm for updating both the translational coordinates and angular velocities. Once the angular velocities are obtained, the angular orientations are updated via the mid-point implicit formula employing the Euler parameters. When the two algorithms, namely, the two-stage explicit algorithm for the generalized coordinates and the implicit staggered procedure for the constraint Lagrange multipliers, are brought together in a staggered manner, they constitute a staggered explicit-implicit procedure which is summarized in Section 5. Section 6 presents some example problems and discussions concerning several salient features of the staggered MBD solution procedure are offered in Section 7.

Characterization of the uncertainty of divergence time estimation under relaxed molecular clock models using multiple loci.

PubMed

Zhu, Tianqi; Dos Reis, Mario; Yang, Ziheng

2015-03-01

Genetic sequence data provide information about the distances between species or branch lengths in a phylogeny, but not about the absolute divergence times or the evolutionary rates directly. Bayesian methods for dating species divergences estimate times and rates by assigning priors on them. In particular, the prior on times (node ages on the phylogeny) incorporates information in the fossil record to calibrate the molecular tree. Because times and rates are confounded, our posterior time estimates will not approach point values even if an infinite amount of sequence data are used in the analysis. In a previous study we developed a finite-sites theory to characterize the uncertainty in Bayesian divergence time estimation in analysis of large but finite sequence data sets under a strict molecular clock. As most modern clock dating analyses use more than one locus and are conducted under relaxed clock models, here we extend the theory to the case of relaxed clock analysis of data from multiple loci (site partitions). Uncertainty in posterior time estimates is partitioned into three sources: Sampling errors in the estimates of branch lengths in the tree for each locus due to limited sequence length, variation of substitution rates among lineages and among loci, and uncertainty in fossil calibrations. Using a simple but analogous estimation problem involving the multivariate normal distribution, we predict that as the number of loci ([Formula: see text]) goes to infinity, the variance in posterior time estimates decreases and approaches the infinite-data limit at the rate of 1/[Formula: see text], and the limit is independent of the number of sites in the sequence alignment. We then confirmed the predictions by using computer simulation on phylogenies of two or three species, and by analyzing a real genomic data set for six primate species. Our results suggest that with the fossil calibrations fixed, analyzing multiple loci or site partitions is the most effective way for improving the precision of posterior time estimation. However, even if a huge amount of sequence data is analyzed, considerable uncertainty will persist in time estimates. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.

Discovering Link Communities in Complex Networks by an Integer Programming Model and a Genetic Algorithm

PubMed Central

Li, Zhenping; Zhang, Xiang-Sun; Wang, Rui-Sheng; Liu, Hongwei; Zhang, Shihua

2013-01-01

Identification of communities in complex networks is an important topic and issue in many fields such as sociology, biology, and computer science. Communities are often defined as groups of related nodes or links that correspond to functional subunits in the corresponding complex systems. While most conventional approaches have focused on discovering communities of nodes, some recent studies start partitioning links to find overlapping communities straightforwardly. In this paper, we propose a new quantity function for link community identification in complex networks. Based on this quantity function we formulate the link community partition problem into an integer programming model which allows us to partition a complex network into overlapping communities. We further propose a genetic algorithm for link community detection which can partition a network into overlapping communities without knowing the number of communities. We test our model and algorithm on both artificial networks and real-world networks. The results demonstrate that the model and algorithm are efficient in detecting overlapping community structure in complex networks. PMID:24386268

Efficient iteration in data-parallel programs with irregular and dynamically distributed data structures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Littlefield, R.J.

1990-02-01

To implement an efficient data-parallel program on a non-shared memory MIMD multicomputer, data and computations must be properly partitioned to achieve good load balance and locality of reference. Programs with irregular data reference patterns often require irregular partitions. Although good partitions may be easy to determine, they can be difficult or impossible to implement in programming languages that provide only regular data distributions, such as blocked or cyclic arrays. We are developing Onyx, a programming system that provides a shared memory model of distributed data structures and extends the concept of data distribution to include irregular and dynamic distributions. Thismore » provides a powerful means to specify irregular partitions. Perhaps surprisingly, programs using it can also execute efficiently. In this paper, we describe and evaluate the Onyx implementation of a model problem that repeatedly executes an irregular but fixed data reference pattern. On an NCUBE hypercube, the speed of the Onyx implementation is comparable to that of carefully handwritten message-passing code.« less

The measurement of the transmission loss of single leaf walls and panels by an impulse method

NASA Astrophysics Data System (ADS)

Balilah, Y. A.; Gibbs, B. M.

1988-06-01

The standard methods of measurement and rating of sound insulation of panels and walls are generally time-consuming and require expensive and often bulky equipment. In addition, the methods establish only that there has been failure to comply with insulation requirements without indicating the mode of failure. An impulse technique is proposed for the measurement of walls and partitions in situ. The method requires the digital capture of a short duration signal generated by a loudspeaker, and the isolation of the direct component from other reflected and scattered components by time-of-flight methods and windowing. The signal, when transferred from the time to frequency domain by means of fast Fourier transforms, can yield the sound insulation of a partition expressed as a transfer function. Experimental problems in the use of this technique, including those resulting from sphericity of the incident wave front and concentric bending excitation of the partition, are identified and methods proposed for their elimination. Most of the results presented are of single leaf panels subjected to sound at normal incidence, although some measurements were undertaken at oblique incidence. The range of surface densities considered was 7-500 kg/m 2, the highest value corresponding to a brick and plaster wall of thickness 285 mm. Measurement is compared with theoretical prediction, at one-third octave intervals in a frequency range of 100-5000 Hz, or as a continuous function of frequency with a typical resolution of 12·5 Hz. The dynamic range of the measurement equipment sets an upper limit to the measurable transmission loss. For the equipment eventually employed this was represented by a random incidence value of 50 dB.

Uncertainty quantification in flux balance analysis of spatially lumped and distributed models of neuron-astrocyte metabolism.

PubMed

Calvetti, Daniela; Cheng, Yougan; Somersalo, Erkki

2016-12-01

Identifying feasible steady state solutions of a brain energy metabolism model is an inverse problem that allows infinitely many solutions. The characterization of the non-uniqueness, or the uncertainty quantification of the flux balance analysis, is tantamount to identifying the degrees of freedom of the solution. The degrees of freedom of multi-compartment mathematical models for energy metabolism of a neuron-astrocyte complex may offer a key to understand the different ways in which the energetic needs of the brain are met. In this paper we study the uncertainty in the solution, using techniques of linear algebra to identify the degrees of freedom in a lumped model, and Markov chain Monte Carlo methods in its extension to a spatially distributed case. The interpretation of the degrees of freedom in metabolic terms, more specifically, glucose and oxygen partitioning, is then leveraged to derive constraints on the free parameters to guarantee that the model is energetically feasible. We demonstrate how the model can be used to estimate the stoichiometric energy needs of the cells as well as the household energy based on the measured oxidative cerebral metabolic rate of glucose and glutamate cycling. Moreover, our analysis shows that in the lumped model the net direction of lactate dehydrogenase (LDH) in the cells can be deduced from the glucose partitioning between the compartments. The extension of the lumped model to a spatially distributed multi-compartment setting that includes diffusion fluxes from capillary to tissue increases the number of degrees of freedom, requiring the use of statistical sampling techniques. The analysis of the distributed model reveals that some of the conclusions valid for the spatially lumped model, e.g., concerning the LDH activity and glucose partitioning, may no longer hold.

P-HARP: A parallel dynamic spectral partitioner

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sohn, A.; Biswas, R.; Simon, H.D.

1997-05-01

Partitioning unstructured graphs is central to the parallel solution of problems in computational science and engineering. The authors have introduced earlier the sequential version of an inertial spectral partitioner called HARP which maintains the quality of recursive spectral bisection (RSB) while forming the partitions an order of magnitude faster than RSB. The serial HARP is known to be the fastest spectral partitioner to date, three to four times faster than similar partitioners on a variety of meshes. This paper presents a parallel version of HARP, called P-HARP. Two types of parallelism have been exploited: loop level parallelism and recursive parallelism.more » P-HARP has been implemented in MPI on the SGI/Cray T3E and the IBM SP2. Experimental results demonstrate that P-HARP can partition a mesh of over 100,000 vertices into 256 partitions in 0.25 seconds on a 64-processor T3E. Experimental results further show that P-HARP can give nearly a 20-fold speedup on 64 processors. These results indicate that graph partitioning is no longer a major bottleneck that hinders the advancement of computational science and engineering for dynamically-changing real-world applications.« less

Analyzing the Responses of 7-8 Year Olds When Solving Partitioning Problems

ERIC Educational Resources Information Center

Badillo, Edelmira; Font, Vicenç; Edo, Mequè

2015-01-01

We analyze the mathematical solutions of 7- to 8-year-old pupils while individually solving an arithmetic problem. The analysis was based on the "configuration of objects," an instrument derived from the onto-semiotic approach to mathematical knowledge. Results are illustrated through a number of cases. From the analysis of mathematical…

Multidimensional spectral load balancing

DOEpatents

Hendrickson, Bruce A.; Leland, Robert W.

1996-12-24

A method of and apparatus for graph partitioning involving the use of a plurality of eigenvectors of the Laplacian matrix of the graph of the problem for which load balancing is desired. The invention is particularly useful for optimizing parallel computer processing of a problem and for minimizing total pathway lengths of integrated circuits in the design stage.

Oranges, Posters, Ribbons, and Lemonade: Concrete Computational Strategies for Dividing Fractions

ERIC Educational Resources Information Center

Kribs-Zaleta, Christopher M.

2008-01-01

This article describes how sixth-grade students developed concrete models to solve division of fractions story problems. Students developed separate two-step procedures to solve measurement and partitive problems, drawing on invented procedures for division of whole numbers. Errors also tended to be specific to the type of division problem…

Spin Number Coherent States and the Problem of Two Coupled Oscillators

NASA Astrophysics Data System (ADS)

Ojeda-Guillén, D.; Mota, R. D.; Granados, V. D.

2015-07-01

From the definition of the standard Perelomov coherent states we introduce the Perelomov number coherent states for any su(2) Lie algebra. With the displacement operator we apply a similarity transformation to the su(2) generators and construct a new set of operators which also close the su(2) Lie algebra, being the Perelomov number coherent states the new basis for its unitary irreducible representation. We apply our results to obtain the energy spectrum, the eigenstates and the partition function of two coupled oscillators. We show that the eigenstates of two coupled oscillators are the SU(2) Perelomov number coherent states of the two-dimensional harmonic oscillator with an appropriate choice of the coherent state parameters. Supported by SNI-México, COFAA-IPN, EDD-IPN, EDI-IPN, SIP-IPN Project No. 20150935

Positive-unlabeled learning for disease gene identification

PubMed Central

Yang, Peng; Li, Xiao-Li; Mei, Jian-Ping; Kwoh, Chee-Keong; Ng, See-Kiong

2012-01-01

Background: Identifying disease genes from human genome is an important but challenging task in biomedical research. Machine learning methods can be applied to discover new disease genes based on the known ones. Existing machine learning methods typically use the known disease genes as the positive training set P and the unknown genes as the negative training set N (non-disease gene set does not exist) to build classifiers to identify new disease genes from the unknown genes. However, such kind of classifiers is actually built from a noisy negative set N as there can be unknown disease genes in N itself. As a result, the classifiers do not perform as well as they could be. Result: Instead of treating the unknown genes as negative examples in N, we treat them as an unlabeled set U. We design a novel positive-unlabeled (PU) learning algorithm PUDI (PU learning for disease gene identification) to build a classifier using P and U. We first partition U into four sets, namely, reliable negative set RN, likely positive set LP, likely negative set LN and weak negative set WN. The weighted support vector machines are then used to build a multi-level classifier based on the four training sets and positive training set P to identify disease genes. Our experimental results demonstrate that our proposed PUDI algorithm outperformed the existing methods significantly. Conclusion: The proposed PUDI algorithm is able to identify disease genes more accurately by treating the unknown data more appropriately as unlabeled set U instead of negative set N. Given that many machine learning problems in biomedical research do involve positive and unlabeled data instead of negative data, it is possible that the machine learning methods for these problems can be further improved by adopting PU learning methods, as we have done here for disease gene identification. Availability and implementation: The executable program and data are available at http://www1.i2r.a-star.edu.sg/∼xlli/PUDI/PUDI.html. Contact: xlli@i2r.a-star.edu.sg or yang0293@e.ntu.edu.sg Supplementary information: Supplementary Data are available at Bioinformatics online. PMID:22923290

A brief history of partitions of numbers, partition functions and their modern applications

NASA Astrophysics Data System (ADS)

Debnath, Lokenath

2016-04-01

'Number rules the universe.' The Pythagoras 'If you wish to forsee the future of mathematics our course is to study the history and present conditions of the science.' Henri Poincaré 'The primary source (Urqell) of all mathematics are integers.' Hermann Minkowski This paper is written to commemorate the centennial anniversary of the Mathematical Association of America. It deals with a short history of different kinds of natural numbers including triangular, square, pentagonal, hexagonal and k-gonal numbers, and their simple properties and their geometrical representations. Included are Euclid's and Pythagorean's main contributions to elementary number theory with the main contents of the Euclid Elements of the 13-volume masterpiece of mathematical work. This is followed by Euler's new discovery of the additive number theory based on partitions of numbers. Special attention is given to many examples, Euler's theorems on partitions of numbers with geometrical representations of Ferrers' graphs, Young's diagrams, Lagrange's four-square theorem and the celebrated Waring problem. Included are Euler's generating functions for the partitions of numbers, Euler's pentagonal number theorem, Gauss' triangular and square number theorems and the Jacobi triple product identity. Applications of the theory of partitions of numbers to different statistics such as the Bose- Einstein, Fermi- Dirac, Gentile, and Maxwell- Boltzmann statistics are briefly discussed. Special attention is given to pedagogical information through historical approach to number theory so that students and teachers at the school, college and university levels can become familiar with the basic concepts of partitions of numbers, partition functions and their modern applications, and can pursue advanced study and research in analytical and computational number theory.

Nudging physician prescription decisions by partitioning the order set: results of a vignette-based study.

PubMed

Tannenbaum, David; Doctor, Jason N; Persell, Stephen D; Friedberg, Mark W; Meeker, Daniella; Friesema, Elisha M; Goldstein, Noah J; Linder, Jeffrey A; Fox, Craig R

2015-03-01

Healthcare professionals are rapidly adopting electronic health records (EHRs). Within EHRs, seemingly innocuous menu design configurations can influence provider decisions for better or worse. The purpose of this study was to examine whether the grouping of menu items systematically affects prescribing practices among primary care providers. We surveyed 166 primary care providers in a research network of practices in the greater Chicago area, of whom 84 responded (51% response rate). Respondents and non-respondents were similar on all observable dimensions except that respondents were more likely to work in an academic setting. The questionnaire consisted of seven clinical vignettes. Each vignette described typical signs and symptoms for acute respiratory infections, and providers chose treatments from a menu of options. For each vignette, providers were randomly assigned to one of two menu partitions. For antibiotic-inappropriate vignettes, the treatment menu either listed over-the-counter (OTC) medications individually while grouping prescriptions together, or displayed the reverse partition. For antibiotic-appropriate vignettes, the treatment menu either listed narrow-spectrum antibiotics individually while grouping broad-spectrum antibiotics, or displayed the reverse partition. The main outcome was provider treatment choice. For antibiotic-inappropriate vignettes, we categorized responses as prescription drugs or OTC-only options. For antibiotic-appropriate vignettes, we categorized responses as broad- or narrow-spectrum antibiotics. Across vignettes, there was an 11.5 percentage point reduction in choosing aggressive treatment options (e.g., broad-spectrum antibiotics) when aggressive options were grouped compared to when those same options were listed individually (95% CI: 2.9 to 20.1%; p = .008). Provider treatment choice appears to be influenced by the grouping of menu options, suggesting that the layout of EHR order sets is not an arbitrary exercise. The careful crafting of EHR order sets can serve as an important opportunity to improve patient care without constraining physicians' ability to prescribe what they believe is best for their patients.

Partition dataset according to amino acid type improves the prediction of deleterious non-synonymous SNPs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Jing; Li, Yuan-Yuan; Shanghai Center for Bioinformation Technology, Shanghai 200235

2012-03-02

Highlights: Black-Right-Pointing-Pointer Proper dataset partition can improve the prediction of deleterious nsSNPs. Black-Right-Pointing-Pointer Partition according to original residue type at nsSNP is a good criterion. Black-Right-Pointing-Pointer Similar strategy is supposed promising in other machine learning problems. -- Abstract: Many non-synonymous SNPs (nsSNPs) are associated with diseases, and numerous machine learning methods have been applied to train classifiers for sorting disease-associated nsSNPs from neutral ones. The continuously accumulated nsSNP data allows us to further explore better prediction approaches. In this work, we partitioned the training data into 20 subsets according to either original or substituted amino acid type at the nsSNPmore » site. Using support vector machine (SVM), training classification models on each subset resulted in an overall accuracy of 76.3% or 74.9% depending on the two different partition criteria, while training on the whole dataset obtained an accuracy of only 72.6%. Moreover, the dataset was also randomly divided into 20 subsets, but the corresponding accuracy was only 73.2%. Our results demonstrated that partitioning the whole training dataset into subsets properly, i.e., according to the residue type at the nsSNP site, will improve the performance of the trained classifiers significantly, which should be valuable in developing better tools for predicting the disease-association of nsSNPs.« less

AN INTEGRATED APPROACH TO CHARACTERIZING BYPASSED OIL IN HETEROGENEOUS AND FRACTURED RESERVOIRS USING PARTITIONING TRACERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akhil Datta-Gupta

2003-08-01

We explore the use of efficient streamline-based simulation approaches for modeling partitioning interwell tracer tests in hydrocarbon reservoirs. Specifically, we utilize the unique features of streamline models to develop an efficient approach for interpretation and history matching of field tracer response. A critical aspect here is the underdetermined and highly ill-posed nature of the associated inverse problems. We have adopted an integrated approach whereby we combine data from multiple sources to minimize the uncertainty and non-uniqueness in the interpreted results. For partitioning interwell tracer tests, these are primarily the distribution of reservoir permeability and oil saturation distribution. A novel approachmore » to multiscale data integration using Markov Random Fields (MRF) has been developed to integrate static data sources from the reservoir such as core, well log and 3-D seismic data. We have also explored the use of a finite difference reservoir simulator, UTCHEM, for field-scale design and optimization of partitioning interwell tracer tests. The finite-difference model allows us to include detailed physics associated with reactive tracer transport, particularly those related with transverse and cross-streamline mechanisms. We have investigated the potential use of downhole tracer samplers and also the use of natural tracers for the design of partitioning tracer tests. Finally, the behavior of partitioning tracer tests in fractured reservoirs is investigated using a dual-porosity finite-difference model.« less

A performance study of sparse Cholesky factorization on INTEL iPSC/860

NASA Technical Reports Server (NTRS)

Zubair, M.; Ghose, M.

1992-01-01

The problem of Cholesky factorization of a sparse matrix has been very well investigated on sequential machines. A number of efficient codes exist for factorizing large unstructured sparse matrices. However, there is a lack of such efficient codes on parallel machines in general, and distributed machines in particular. Some of the issues that are critical to the implementation of sparse Cholesky factorization on a distributed memory parallel machine are ordering, partitioning and mapping, load balancing, and ordering of various tasks within a processor. Here, we focus on the effect of various partitioning schemes on the performance of sparse Cholesky factorization on the Intel iPSC/860. Also, a new partitioning heuristic for structured as well as unstructured sparse matrices is proposed, and its performance is compared with other schemes.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Slattery, Stuart R.

In this study we analyze and extend mesh-free algorithms for three-dimensional data transfer problems in partitioned multiphysics simulations. We first provide a direct comparison between a mesh-based weighted residual method using the common-refinement scheme and two mesh-free algorithms leveraging compactly supported radial basis functions: one using a spline interpolation and one using a moving least square reconstruction. Through the comparison we assess both the conservation and accuracy of the data transfer obtained from each of the methods. We do so for a varying set of geometries with and without curvature and sharp features and for functions with and without smoothnessmore » and with varying gradients. Our results show that the mesh-based and mesh-free algorithms are complementary with cases where each was demonstrated to perform better than the other. We then focus on the mesh-free methods by developing a set of algorithms to parallelize them based on sparse linear algebra techniques. This includes a discussion of fast parallel radius searching in point clouds and restructuring the interpolation algorithms to leverage data structures and linear algebra services designed for large distributed computing environments. The scalability of our new algorithms is demonstrated on a leadership class computing facility using a set of basic scaling studies. Finally, these scaling studies show that for problems with reasonable load balance, our new algorithms for both spline interpolation and moving least square reconstruction demonstrate both strong and weak scalability using more than 100,000 MPI processes with billions of degrees of freedom in the data transfer operation.« less

Adaptive hybrid simulations for multiscale stochastic reaction networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

2015-01-21

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such amore » partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.« less

Adaptive hybrid simulations for multiscale stochastic reaction networks.

PubMed

Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

2015-01-21

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information.

PubMed

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft's algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms.

Correspondence between spanning trees and the Ising model on a square lattice

NASA Astrophysics Data System (ADS)

Viswanathan, G. M.

2017-06-01

An important problem in statistical physics concerns the fascinating connections between partition functions of lattice models studied in equilibrium statistical mechanics on the one hand and graph theoretical enumeration problems on the other hand. We investigate the nature of the relationship between the number of spanning trees and the partition function of the Ising model on the square lattice. The spanning tree generating function T (z ) gives the spanning tree constant when evaluated at z =1 , while giving the lattice green function when differentiated. It is known that for the infinite square lattice the partition function Z (K ) of the Ising model evaluated at the critical temperature K =Kc is related to T (1 ) . Here we show that this idea in fact generalizes to all real temperatures. We prove that [Z(K ) s e c h 2 K ] 2=k exp[T (k )] , where k =2 tanh(2 K )s e c h (2 K ) . The identical Mahler measure connects the two seemingly disparate quantities T (z ) and Z (K ) . In turn, the Mahler measure is determined by the random walk structure function. Finally, we show that the the above correspondence does not generalize in a straightforward manner to nonplanar lattices.

On the Problem of Bandwidth Partitioning in FDD Block-Fading Single-User MISO/SIMO Systems

NASA Astrophysics Data System (ADS)

Ivrlač, Michel T.; Nossek, Josef A.

2008-12-01

We report on our research activity on the problem of how to optimally partition the available bandwidth of frequency division duplex, multi-input single-output communication systems, into subbands for the uplink, the downlink, and the feedback. In the downlink, the transmitter applies coherent beamforming based on quantized channel information which is obtained by feedback from the receiver. As feedback takes away resources from the uplink, which could otherwise be used to transfer payload data, it is highly desirable to reserve the "right" amount of uplink resources for the feedback. Under the assumption of random vector quantization, and a frequency flat, independent and identically distributed block-fading channel, we derive closed-form expressions for both the feedback quantization and bandwidth partitioning which jointly maximize the sum of the average payload data rates of the downlink and the uplink. While we do introduce some approximations to facilitate mathematical tractability, the analytical solution is asymptotically exact as the number of antennas approaches infinity, while for systems with few antennas, it turns out to be a fairly accurate approximation. In this way, the obtained results are meaningful for practical communication systems, which usually can only employ a few antennas.

Evolutionary Computation with Spatial Receding Horizon Control to Minimize Network Coding Resources

PubMed Central

Leeson, Mark S.

2014-01-01

The minimization of network coding resources, such as coding nodes and links, is a challenging task, not only because it is a NP-hard problem, but also because the problem scale is huge; for example, networks in real world may have thousands or even millions of nodes and links. Genetic algorithms (GAs) have a good potential of resolving NP-hard problems like the network coding problem (NCP), but as a population-based algorithm, serious scalability and applicability problems are often confronted when GAs are applied to large- or huge-scale systems. Inspired by the temporal receding horizon control in control engineering, this paper proposes a novel spatial receding horizon control (SRHC) strategy as a network partitioning technology, and then designs an efficient GA to tackle the NCP. Traditional network partitioning methods can be viewed as a special case of the proposed SRHC, that is, one-step-wide SRHC, whilst the method in this paper is a generalized N-step-wide SRHC, which can make a better use of global information of network topologies. Besides the SRHC strategy, some useful designs are also reported in this paper. The advantages of the proposed SRHC and GA for the NCP are illustrated by extensive experiments, and they have a good potential of being extended to other large-scale complex problems. PMID:24883371

Time-independent hybrid enrichment for finite element solution of transient conduction–radiation in diffusive grey media

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mohamed, M. Shadi, E-mail: m.s.mohamed@durham.ac.uk; Seaid, Mohammed; Trevelyan, Jon

2013-10-15

We investigate the effectiveness of the partition-of-unity finite element method for transient conduction–radiation problems in diffusive grey media. The governing equations consist of a semi-linear transient heat equation for the temperature field and a stationary diffusion approximation to the radiation in grey media. The coupled equations are integrated in time using a semi-implicit method in the finite element framework. We show that for the considered problems, a combination of hyperbolic and exponential enrichment functions based on an approximation of the boundary layer leads to improved accuracy compared to the conventional finite element method. It is illustrated that this approach canmore » be more efficient than using h adaptivity to increase the accuracy of the finite element method near the boundary walls. The performance of the proposed partition-of-unity method is analyzed on several test examples for transient conduction–radiation problems in two space dimensions.« less

Partitioning net ecosystem carbon exchange into net assimilation and respiration using 13CO2 measurements: A cost-effective sampling strategy

NASA Astrophysics Data System (ADS)

OgéE, J.; Peylin, P.; Ciais, P.; Bariac, T.; Brunet, Y.; Berbigier, P.; Roche, C.; Richard, P.; Bardoux, G.; Bonnefond, J.-M.

2003-06-01

The current emphasis on global climate studies has led the scientific community to set up a number of sites for measuring the long-term biosphere-atmosphere net CO2 exchange (net ecosystem exchange, NEE). Partitioning this flux into its elementary components, net assimilation (FA), and respiration (FR), remains necessary in order to get a better understanding of biosphere functioning and design better surface exchange models. Noting that FR and FA have different isotopic signatures, we evaluate the potential of isotopic 13CO2 measurements in the air (combined with CO2 flux and concentration measurements) to partition NEE into FR and FA on a routine basis. The study is conducted at a temperate coniferous forest where intensive isotopic measurements in air, soil, and biomass were performed in summer 1997. The multilayer soil-vegetation-atmosphere transfer model MuSICA is adapted to compute 13CO2 flux and concentration profiles. Using MuSICA as a "perfect" simulator and taking advantage of the very dense spatiotemporal resolution of the isotopic data set (341 flasks over a 24-hour period) enable us to test each hypothesis and estimate the performance of the method. The partitioning works better in midafternoon when isotopic disequilibrium is strong. With only 15 flasks, i.e., two 13CO2 nighttime profiles (to estimate the isotopic signature of FR) and five daytime measurements (to perform the partitioning) we get mean daily estimates of FR and FA that agree with the model within 15-20%. However, knowledge of the mesophyll conductance seems crucial and may be a limitation to the method.

Influence of Silicate Melt Composition on Metal/Silicate Partitioning of W, Ge, Ga and Ni

NASA Technical Reports Server (NTRS)

Singletary, S. J.; Domanik, K.; Drake, M. J.

2005-01-01

The depletion of the siderophile elements in the Earth's upper mantle relative to the chondritic meteorites is a geochemical imprint of core segregation. Therefore, metal/silicate partition coefficients (Dm/s) for siderophile elements are essential to investigations of core formation when used in conjunction with the pattern of elemental abundances in the Earth's mantle. The partitioning of siderophile elements is controlled by temperature, pressure, oxygen fugacity, and by the compositions of the metal and silicate phases. Several recent studies have shown the importance of silicate melt composition on the partitioning of siderophile elements between silicate and metallic liquids. It has been demonstrated that many elements display increased solubility in less polymerized (mafic) melts. However, the importance of silicate melt composition was believed to be minor compared to the influence of oxygen fugacity until studies showed that melt composition is an important factor at high pressures and temperatures. It was found that melt composition is also important for partitioning of high valency siderophile elements. Atmospheric experiments were conducted, varying only silicate melt composition, to assess the importance of silicate melt composition for the partitioning of W, Co and Ga and found that the valence of the dissolving species plays an important role in determining the effect of composition on solubility. In this study, we extend the data set to higher pressures and investigate the role of silicate melt composition on the partitioning of the siderophile elements W, Ge, Ga and Ni between metallic and silicate liquid.

Improving Design Efficiency for Large-Scale Heterogeneous Circuits

NASA Astrophysics Data System (ADS)

Gregerson, Anthony

Despite increases in logic density, many Big Data applications must still be partitioned across multiple computing devices in order to meet their strict performance requirements. Among the most demanding of these applications is high-energy physics (HEP), which uses complex computing systems consisting of thousands of FPGAs and ASICs to process the sensor data created by experiments at particles accelerators such as the Large Hadron Collider (LHC). Designing such computing systems is challenging due to the scale of the systems, the exceptionally high-throughput and low-latency performance constraints that necessitate application-specific hardware implementations, the requirement that algorithms are efficiently partitioned across many devices, and the possible need to update the implemented algorithms during the lifetime of the system. In this work, we describe our research to develop flexible architectures for implementing such large-scale circuits on FPGAs. In particular, this work is motivated by (but not limited in scope to) high-energy physics algorithms for the Compact Muon Solenoid (CMS) experiment at the LHC. To make efficient use of logic resources in multi-FPGA systems, we introduce Multi-Personality Partitioning, a novel form of the graph partitioning problem, and present partitioning algorithms that can significantly improve resource utilization on heterogeneous devices while also reducing inter-chip connections. To reduce the high communication costs of Big Data applications, we also introduce Information-Aware Partitioning, a partitioning method that analyzes the data content of application-specific circuits, characterizes their entropy, and selects circuit partitions that enable efficient compression of data between chips. We employ our information-aware partitioning method to improve the performance of the hardware validation platform for evaluating new algorithms for the CMS experiment. Together, these research efforts help to improve the efficiency and decrease the cost of the developing large-scale, heterogeneous circuits needed to enable large-scale application in high-energy physics and other important areas.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks.

PubMed

Sung, Yoonyoung; Lee, Sookyoung; Lee, Meejeong

2018-03-23

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63-87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6-89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network.

A Multi-Hop Clustering Mechanism for Scalable IoT Networks

PubMed Central

2018-01-01

It is expected that up to 26 billion Internet of Things (IoT) equipped with sensors and wireless communication capabilities will be connected to the Internet by 2020 for various purposes. With a large scale IoT network, having each node connected to the Internet with an individual connection may face serious scalability issues. The scalability problem of the IoT network may be alleviated by grouping the nodes of the IoT network into clusters and having a representative node in each cluster connect to the Internet on behalf of the other nodes in the cluster instead of having a per-node Internet connection and communication. In this paper, we propose a multi-hop clustering mechanism for IoT networks to minimize the number of required Internet connections. Specifically, the objective of proposed mechanism is to select the minimum number of coordinators, which take the role of a representative node for the cluster, i.e., having the Internet connection on behalf of the rest of the nodes in the cluster and to map a partition of the IoT nodes onto the selected set of coordinators to minimize the total distance between the nodes and their respective coordinator under a certain constraint in terms of maximum hop count between the IoT nodes and their respective coordinator. Since this problem can be mapped into a set cover problem which is known as NP-hard, we pursue a heuristic approach to solve the problem and analyze the complexity of the proposed solution. Through a set of experiments with varying parameters, the proposed scheme shows 63–87.3% reduction of the Internet connections depending on the number of the IoT nodes while that of the optimal solution is 65.6–89.9% in a small scale network. Moreover, it is shown that the performance characteristics of the proposed mechanism coincide with expected performance characteristics of the optimal solution in a large-scale network. PMID:29570691

Handling of computational in vitro/in vivo correlation problems by Microsoft Excel: V. Predictive absorbability models.

PubMed

Langenbucher, Frieder

2007-08-01

This paper discusses Excel applications related to the prediction of drug absorbability from physicochemical constants. PHDISSOC provides a generalized model for pH profiles of electrolytic dissociation, water solubility, and partition coefficient. SKMODEL predicts drug absorbability, based on a log-log plot of water solubility and O/W partitioning; augmented by additional features such as electrolytic dissociation, melting point, and the dose administered. GIABS presents a mechanistic model of g.i. drug absorption. BIODATCO presents a database compiling relevant drug data to be used for quantitative predictions.

A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics

PubMed Central

Kerfriden, P.; Goury, O.; Rabczuk, T.; Bordas, S.P.A.

2013-01-01

We propose in this paper a reduced order modelling technique based on domain partitioning for parametric problems of fracture. We show that coupling domain decomposition and projection-based model order reduction permits to focus the numerical effort where it is most needed: around the zones where damage propagates. No a priori knowledge of the damage pattern is required, the extraction of the corresponding spatial regions being based solely on algebra. The efficiency of the proposed approach is demonstrated numerically with an example relevant to engineering fracture. PMID:23750055

Solving Multi-variate Polynomial Equations in a Finite Field

DTIC Science & Technology

2013-06-01

Algebraic Background In this section, some algebraic definitions and basics are discussed as they pertain to this re- search. For a more detailed...definitions and basics are discussed as they pertain to this research. For a more detailed treatment, consult a graph theory text such as [10]. A graph G...graph if V(G) can be partitioned into k subsets V1,V2, ...,Vk such that uv is only an edge of G if u and v belong to different partite sets. If, in

Dimensionally regularized Tsallis' statistical mechanics and two-body Newton's gravitation

NASA Astrophysics Data System (ADS)

Zamora, J. D.; Rocca, M. C.; Plastino, A.; Ferri, G. L.

2018-05-01

Typical Tsallis' statistical mechanics' quantifiers like the partition function and the mean energy exhibit poles. We are speaking of the partition function Z and the mean energy 〈 U 〉 . The poles appear for distinctive values of Tsallis' characteristic real parameter q, at a numerable set of rational numbers of the q-line. These poles are dealt with dimensional regularization resources. The physical effects of these poles on the specific heats are studied here for the two-body classical gravitation potential.

H-PoP and H-PoPG: heuristic partitioning algorithms for single individual haplotyping of polyploids.

PubMed

Xie, Minzhu; Wu, Qiong; Wang, Jianxin; Jiang, Tao

2016-12-15

Some economically important plants including wheat and cotton have more than two copies of each chromosome. With the decreasing cost and increasing read length of next-generation sequencing technologies, reconstructing the multiple haplotypes of a polyploid genome from its sequence reads becomes practical. However, the computational challenge in polyploid haplotyping is much greater than that in diploid haplotyping, and there are few related methods. This article models the polyploid haplotyping problem as an optimal poly-partition problem of the reads, called the Polyploid Balanced Optimal Partition model. For the reads sequenced from a k-ploid genome, the model tries to divide the reads into k groups such that the difference between the reads of the same group is minimized while the difference between the reads of different groups is maximized. When the genotype information is available, the model is extended to the Polyploid Balanced Optimal Partition with Genotype constraint problem. These models are all NP-hard. We propose two heuristic algorithms, H-PoP and H-PoPG, based on dynamic programming and a strategy of limiting the number of intermediate solutions at each iteration, to solve the two models, respectively. Extensive experimental results on simulated and real data show that our algorithms can solve the models effectively, and are much faster and more accurate than the recent state-of-the-art polyploid haplotyping algorithms. The experiments also show that our algorithms can deal with long reads and deep read coverage effectively and accurately. Furthermore, H-PoP might be applied to help determine the ploidy of an organism. https://github.com/MinzhuXie/H-PoPG CONTACT: xieminzhu@hotmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Parallel deterministic transport sweeps of structured and unstructured meshes with overloaded mesh decompositions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pautz, Shawn D.; Bailey, Teresa S.

Here, the efficiency of discrete ordinates transport sweeps depends on the scheduling algorithm, the domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amountmore » of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 10 5 processor cores.« less

Venous tree separation in the liver: graph partitioning using a non-ising model.

PubMed

O'Donnell, Thomas; Kaftan, Jens N; Schuh, Andreas; Tietjen, Christian; Soza, Grzegorz; Aach, Til

2011-01-01

Entangled tree-like vascular systems are commonly found in the body (e.g., in the peripheries and lungs). Separation of these systems in medical images may be formulated as a graph partitioning problem given an imperfect segmentation and specification of the tree roots. In this work, we show that the ubiquitous Ising-model approaches (e.g., Graph Cuts, Random Walker) are not appropriate for tackling this problem and propose a novel method based on recursive minimal paths for doing so. To motivate our method, we focus on the intertwined portal and hepatic venous systems in the liver. Separation of these systems is critical for liver intervention planning, in particular when resection is involved. We apply our method to 34 clinical datasets, each containing well over a hundred vessel branches, demonstrating its effectiveness.

Parallel deterministic transport sweeps of structured and unstructured meshes with overloaded mesh decompositions

DOE PAGES

Pautz, Shawn D.; Bailey, Teresa S.

2016-11-29

Here, the efficiency of discrete ordinates transport sweeps depends on the scheduling algorithm, the domain decomposition, the problem to be solved, and the computational platform. Sweep scheduling algorithms may be categorized by their approach to several issues. In this paper we examine the strategy of domain overloading for mesh partitioning as one of the components of such algorithms. In particular, we extend the domain overloading strategy, previously defined and analyzed for structured meshes, to the general case of unstructured meshes. We also present computational results for both the structured and unstructured domain overloading cases. We find that an appropriate amountmore » of domain overloading can greatly improve the efficiency of parallel sweeps for both structured and unstructured partitionings of the test problems examined on up to 10 5 processor cores.« less

Coordinated platooning with multiple speeds

DOE PAGES

Luo, Fengqiao; Larson, Jeffrey; Munson, Todd

2018-03-22

In a platoon, vehicles travel one after another with small intervehicle distances; trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on themore » time each vehicle is allowed to stay in the network; this time affects vehicles’ available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.« less

Coordinated platooning with multiple speeds

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Fengqiao; Larson, Jeffrey; Munson, Todd

In a platoon, vehicles travel one after another with small intervehicle distances; trailing vehicles in a platoon save fuel because they experience less aerodynamic drag. This work presents a coordinated platooning model with multiple speed options that integrates scheduling, routing, speed selection, and platoon formation/dissolution in a mixed-integer linear program that minimizes the total fuel consumed by a set of vehicles while traveling between their respective origins and destinations. The performance of this model is numerically tested on a grid network and the Chicago-area highway network. We find that the fuel-savings factor of a multivehicle system significantly depends on themore » time each vehicle is allowed to stay in the network; this time affects vehicles’ available speed choices, possible routes, and the amount of time for coordinating platoon formation. For problem instances with a large number of vehicles, we propose and test a heuristic decomposed approach that applies a clustering algorithm to partition the set of vehicles and then routes each group separately. When the set of vehicles is large and the available computational time is small, the decomposed approach finds significantly better solutions than does the full model.« less

Two-lattice models of trace element behavior: A response

NASA Astrophysics Data System (ADS)

Ellison, Adam J. G.; Hess, Paul C.

1990-08-01

Two-lattice melt components of Bottinga and Weill (1972), Nielsen and Drake (1979), and Nielsen (1985) are applied to major and trace element partitioning between coexisting immiscible liquids studied by RYERSON and Hess (1978) and Watson (1976). The results show that (1) the set of components most successful in one system is not necessarily portable to another system; (2) solution non-ideality within a sublattice severely limits applicability of two-lattice models; (3) rigorous application of two-lattice melt components may yield effective partition coefficients for major element components with no physical interpretation; and (4) the distinction between network-forming and network-modifying components in the sense of the two-lattice models is not clear cut. The algebraic description of two-lattice models is such that they will most successfully limit the compositional dependence of major and trace element solution behavior when the effective partition coefficient of the component of interest is essentially the same as the bulk partition coefficient of all other components within its sublattice.

Toward prediction of alkane/water partition coefficients.

PubMed

Toulmin, Anita; Wood, J Matthew; Kenny, Peter W

2008-07-10

Partition coefficients were measured for 47 compounds in the hexadecane/water ( P hxd) and 1-octanol/water ( P oct) systems. Some types of hydrogen bond acceptor presented by these compounds to the partitioning systems are not well represented in the literature of alkane/water partitioning. The difference, DeltalogP, between logP oct and logP hxd is a measure of the hydrogen bonding potential of a molecule and is identified as a target for predictive modeling. Minimized molecular electrostatic potential ( V min) was shown to be an effective predictor of the contribution of hydrogen bond acceptors to DeltalogP. Carbonyl oxygen atoms were found to be stronger hydrogen bond acceptors for their electrostatic potential than heteroaromatic nitrogen or oxygen bound to hypervalent sulfur or nitrogen. Values of V min calculated for hydrogen-bonded complexes were used to explore polarization effects. Predicted logP hxd and DeltalogP were shown to be more effective than logP oct for modeling brain penetration for a data set of 18 compounds.

Sharing the cell's bounty - organelle inheritance in yeast.

PubMed

Knoblach, Barbara; Rachubinski, Richard A

2015-02-15

Eukaryotic cells replicate and partition their organelles between the mother cell and the daughter cell at cytokinesis. Polarized cells, notably the budding yeast Saccharomyces cerevisiae, are well suited for the study of organelle inheritance, as they facilitate an experimental dissection of organelle transport and retention processes. Much progress has been made in defining the molecular players involved in organelle partitioning in yeast. Each organelle uses a distinct set of factors - motor, anchor and adaptor proteins - that ensures its inheritance by future generations of cells. We propose that all organelles, regardless of origin or copy number, are partitioned by the same fundamental mechanism involving division and segregation. Thus, the mother cell keeps, and the daughter cell receives, their fair and equitable share of organelles. This mechanism of partitioning moreover facilitates the segregation of organelle fragments that are not functionally equivalent. In this Commentary, we describe how this principle of organelle population control affects peroxisomes and other organelles, and outline its implications for yeast life span and rejuvenation. © 2015. Published by The Company of Biologists Ltd.

Partitioning of polar and non-polar neutral organic chemicals into human and cow milk.

PubMed

Geisler, Anett; Endo, Satoshi; Goss, Kai-Uwe

2011-10-01

The aim of this work was to develop a predictive model for milk/water partition coefficients of neutral organic compounds. Batch experiments were performed for 119 diverse organic chemicals in human milk and raw and processed cow milk at 37°C. No differences (<0.3 log units) in the partition coefficients of these types of milk were observed. The polyparameter linear free energy relationship model fit the calibration data well (SD=0.22 log units). An experimental validation data set including hormones and hormone active compounds was predicted satisfactorily by the model. An alternative modelling approach based on log K(ow) revealed a poorer performance. The model presented here provides a significant improvement in predicting enrichment of potentially hazardous chemicals in milk. In combination with physiologically based pharmacokinetic modelling this improvement in the estimation of milk/water partitioning coefficients may allow a better risk assessment for a wide range of neutral organic chemicals. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Geographic Optimization Approach to Coast Guard Ship Basing

DTIC Science & Technology

2015-06-01

information found an optimal result for partition- ing. Carlsson applies the travelling salesman problem (tries to find the shortest path to visit a list of...maximum 200 words) This thesis studies the problem of finding efficient ship base locations, area of operations (AO) among bases, and ship assignments...for a coast guard (CG) organization. This problem is faced by many CGs around the world and is motivated by the need to optimize operational outcomes

The "p"-Median Model as a Tool for Clustering Psychological Data

ERIC Educational Resources Information Center

Kohn, Hans-Friedrich; Steinley, Douglas; Brusco, Michael J.

2010-01-01

The "p"-median clustering model represents a combinatorial approach to partition data sets into disjoint, nonhierarchical groups. Object classes are constructed around "exemplars", that is, manifest objects in the data set, with the remaining instances assigned to their closest cluster centers. Effective, state-of-the-art implementations of…

Partitioning of residual D-limonene cleaner vapor among organic materials in weapons

DOE Office of Scientific and Technical Information (OSTI.GOV)

LeMay, J.D.

1993-03-01

D-limonene is a replacement solvent selected by Sandia and Allied-Signal to clean solder flux from electronics assemblies in firesets and programmers. D-limonene is much slower drying than the solvents it has replaced and this has raised concerns that residual quantities of the cleaner could be trapped in the electronics assemblies and eventually carried into warhead assemblies. This paper describes a study designed to evaluate how vapors from residual d-limonene cleaner would be partitioned among typical organic materials in a Livermore device. The goal was to identify possible compatibility problems arising from the use of d-limonene and, in particular, any interactionsmore » it may have with energetic materials. To predict the partitioning behavior of d-limonene, a simple model was developed and its predictions are compared to the experimental findings.« less

Automatic selection of dynamic data partitioning schemes for distributed memory multicomputers

NASA Technical Reports Server (NTRS)

Palermo, Daniel J.; Banerjee, Prithviraj

1995-01-01

For distributed memory multicomputers such as the Intel Paragon, the IBM SP-2, the NCUBE/2, and the Thinking Machines CM-5, the quality of the data partitioning for a given application is crucial to obtaining high performance. This task has traditionally been the user's responsibility, but in recent years much effort has been directed to automating the selection of data partitioning schemes. Several researchers have proposed systems that are able to produce data distributions that remain in effect for the entire execution of an application. For complex programs, however, such static data distributions may be insufficient to obtain acceptable performance. The selection of distributions that dynamically change over the course of a program's execution adds another dimension to the data partitioning problem. In this paper, we present a technique that can be used to automatically determine which partitionings are most beneficial over specific sections of a program while taking into account the added overhead of performing redistribution. This system is being built as part of the PARADIGM (PARAllelizing compiler for DIstributed memory General-purpose Multicomputers) project at the University of Illinois. The complete system will provide a fully automated means to parallelize programs written in a serial programming model obtaining high performance on a wide range of distributed-memory multicomputers.

A stable and accurate partitioned algorithm for conjugate heat transfer

NASA Astrophysics Data System (ADS)

Meng, F.; Banks, J. W.; Henshaw, W. D.; Schwendeman, D. W.

2017-09-01

We describe a new partitioned approach for solving conjugate heat transfer (CHT) problems where the governing temperature equations in different material domains are time-stepped in an implicit manner, but where the interface coupling is explicit. The new approach, called the CHAMP scheme (Conjugate Heat transfer Advanced Multi-domain Partitioned), is based on a discretization of the interface coupling conditions using a generalized Robin (mixed) condition. The weights in the Robin condition are determined from the optimization of a condition derived from a local stability analysis of the coupling scheme. The interface treatment combines ideas from optimized-Schwarz methods for domain-decomposition problems together with the interface jump conditions and additional compatibility jump conditions derived from the governing equations. For many problems (i.e. for a wide range of material properties, grid-spacings and time-steps) the CHAMP algorithm is stable and second-order accurate using no sub-time-step iterations (i.e. a single implicit solve of the temperature equation in each domain). In extreme cases (e.g. very fine grids with very large time-steps) it may be necessary to perform one or more sub-iterations. Each sub-iteration generally increases the range of stability substantially and thus one sub-iteration is likely sufficient for the vast majority of practical problems. The CHAMP algorithm is developed first for a model problem and analyzed using normal-mode theory. The theory provides a mechanism for choosing optimal parameters in the mixed interface condition. A comparison is made to the classical Dirichlet-Neumann (DN) method and, where applicable, to the optimized-Schwarz (OS) domain-decomposition method. For problems with different thermal conductivities and diffusivities, the CHAMP algorithm outperforms the DN scheme. For domain-decomposition problems with uniform conductivities and diffusivities, the CHAMP algorithm performs better than the typical OS scheme with one grid-cell overlap. The CHAMP scheme is also developed for general curvilinear grids and CHT examples are presented using composite overset grids that confirm the theory and demonstrate the effectiveness of the approach.

A stable and accurate partitioned algorithm for conjugate heat transfer

DOE PAGES

Meng, F.; Banks, J. W.; Henshaw, W. D.; ...

2017-04-25

We describe a new partitioned approach for solving conjugate heat transfer (CHT) problems where the governing temperature equations in different material domains are time-stepped in a implicit manner, but where the interface coupling is explicit. The new approach, called the CHAMP scheme (Conjugate Heat transfer Advanced Multi-domain Partitioned), is based on a discretization of the interface coupling conditions using a generalized Robin (mixed) condition. The weights in the Robin condition are determined from the optimization of a condition derived from a local stability analysis of the coupling scheme. The interface treatment combines ideas from optimized-Schwarz methods for domain-decomposition problems togethermore » with the interface jump conditions and additional compatibility jump conditions derived from the governing equations. For many problems (i.e. for a wide range of material properties, grid-spacings and time-steps) the CHAMP algorithm is stable and second-order accurate using no sub-time-step iterations (i.e. a single implicit solve of the temperature equation in each domain). In extreme cases (e.g. very fine grids with very large time-steps) it may be necessary to perform one or more sub-iterations. Each sub-iteration generally increases the range of stability substantially and thus one sub-iteration is likely sufficient for the vast majority of practical problems. The CHAMP algorithm is developed first for a model problem and analyzed using normal-mode the- ory. The theory provides a mechanism for choosing optimal parameters in the mixed interface condition. A comparison is made to the classical Dirichlet-Neumann (DN) method and, where applicable, to the optimized- Schwarz (OS) domain-decomposition method. For problems with different thermal conductivities and dif- fusivities, the CHAMP algorithm outperforms the DN scheme. For domain-decomposition problems with uniform conductivities and diffusivities, the CHAMP algorithm performs better than the typical OS scheme with one grid-cell overlap. Lastly, the CHAMP scheme is also developed for general curvilinear grids and CHT ex- amples are presented using composite overset grids that confirm the theory and demonstrate the effectiveness of the approach.« less

A partitioned correlation function interaction approach for describing electron correlation in atoms

NASA Astrophysics Data System (ADS)

Verdebout, S.; Rynkun, P.; Jönsson, P.; Gaigalas, G.; Froese Fischer, C.; Godefroid, M.

2013-04-01

The traditional multiconfiguration Hartree-Fock (MCHF) and configuration interaction (CI) methods are based on a single orthonormal orbital basis. For atoms with many closed core shells, or complicated shell structures, a large orbital basis is needed to saturate the different electron correlation effects such as valence, core-valence and correlation within the core shells. The large orbital basis leads to massive configuration state function (CSF) expansions that are difficult to handle, even on large computer systems. We show that it is possible to relax the orthonormality restriction on the orbital basis and break down the originally very large calculations into a series of smaller calculations that can be run in parallel. Each calculation determines a partitioned correlation function (PCF) that accounts for a specific correlation effect. The PCFs are built on optimally localized orbital sets and are added to a zero-order multireference (MR) function to form a total wave function. The expansion coefficients of the PCFs are determined from a low dimensional generalized eigenvalue problem. The interaction and overlap matrices are computed using a biorthonormal transformation technique (Verdebout et al 2010 J. Phys. B: At. Mol. Phys. 43 074017). The new method, called partitioned correlation function interaction (PCFI), converges rapidly with respect to the orbital basis and gives total energies that are lower than the ones from ordinary MCHF and CI calculations. The PCFI method is also very flexible when it comes to targeting different electron correlation effects. Focusing our attention on neutral lithium, we show that by dedicating a PCF to the single excitations from the core, spin- and orbital-polarization effects can be captured very efficiently, leading to highly improved convergence patterns for hyperfine parameters compared with MCHF calculations based on a single orthogonal radial orbital basis. By collecting separately optimized PCFs to correct the MR function, the variational degrees of freedom in the relative mixing coefficients of the CSFs building the PCFs are inhibited. The constraints on the mixing coefficients lead to small off-sets in computed properties such as hyperfine structure, isotope shift and transition rates, with respect to the correct values. By (partially) deconstraining the mixing coefficients one converges to the correct limits and keeps the tremendous advantage of improved convergence rates that comes from the use of several orbital sets. Reducing ultimately each PCF to a single CSF with its own orbital basis leads to a non-orthogonal CI approach. Various perspectives of the new method are given.

Spectral (Finite) Volume Method for Conservation Laws on Unstructured Grids II: Extension to Two Dimensional Scalar Equation

NASA Technical Reports Server (NTRS)

Wang, Z. J.; Liu, Yen; Kwak, Dochan (Technical Monitor)

2002-01-01

The framework for constructing a high-order, conservative Spectral (Finite) Volume (SV) method is presented for two-dimensional scalar hyperbolic conservation laws on unstructured triangular grids. Each triangular grid cell forms a spectral volume (SV), and the SV is further subdivided into polygonal control volumes (CVs) to supported high-order data reconstructions. Cell-averaged solutions from these CVs are used to reconstruct a high order polynomial approximation in the SV. Each CV is then updated independently with a Godunov-type finite volume method and a high-order Runge-Kutta time integration scheme. A universal reconstruction is obtained by partitioning all SVs in a geometrically similar manner. The convergence of the SV method is shown to depend on how a SV is partitioned. A criterion based on the Lebesgue constant has been developed and used successfully to determine the quality of various partitions. Symmetric, stable, and convergent linear, quadratic, and cubic SVs have been obtained, and many different types of partitions have been evaluated. The SV method is tested for both linear and non-linear model problems with and without discontinuities.

Parallel Clustering Algorithm for Large-Scale Biological Data Sets

PubMed Central

Wang, Minchao; Zhang, Wu; Ding, Wang; Dai, Dongbo; Zhang, Huiran; Xie, Hao; Chen, Luonan; Guo, Yike; Xie, Jiang

2014-01-01

Backgrounds Recent explosion of biological data brings a great challenge for the traditional clustering algorithms. With increasing scale of data sets, much larger memory and longer runtime are required for the cluster identification problems. The affinity propagation algorithm outperforms many other classical clustering algorithms and is widely applied into the biological researches. However, the time and space complexity become a great bottleneck when handling the large-scale data sets. Moreover, the similarity matrix, whose constructing procedure takes long runtime, is required before running the affinity propagation algorithm, since the algorithm clusters data sets based on the similarities between data pairs. Methods Two types of parallel architectures are proposed in this paper to accelerate the similarity matrix constructing procedure and the affinity propagation algorithm. The memory-shared architecture is used to construct the similarity matrix, and the distributed system is taken for the affinity propagation algorithm, because of its large memory size and great computing capacity. An appropriate way of data partition and reduction is designed in our method, in order to minimize the global communication cost among processes. Result A speedup of 100 is gained with 128 cores. The runtime is reduced from serval hours to a few seconds, which indicates that parallel algorithm is capable of handling large-scale data sets effectively. The parallel affinity propagation also achieves a good performance when clustering large-scale gene data (microarray) and detecting families in large protein superfamilies. PMID:24705246

Exact deconstruction of the 6D (2,0) theory

NASA Astrophysics Data System (ADS)

Hayling, J.; Papageorgakis, C.; Pomoni, E.; Rodríguez-Gómez, D.

2017-06-01

The dimensional-deconstruction prescription of Arkani-Hamed, Cohen, Kaplan, Karch and Motl provides a mechanism for recovering the A-type (2,0) theories on T 2, starting from a four-dimensional N=2 circular-quiver theory. We put this conjecture to the test using two exact-counting arguments: in the decompactification limit, we compare the Higgs-branch Hilbert series of the 4D N=2 quiver to the "half-BPS" limit of the (2,0) superconformal index. We also compare the full partition function for the 4D quiver on S 4 to the (2,0) partition function on S 4 × T 2. In both cases we find exact agreement. The partition function calculation sets up a dictionary between exact results in 4D and 6D.

Metatranscriptome analyses indicate resource partitioning between diatoms in the field.

PubMed

Alexander, Harriet; Jenkins, Bethany D; Rynearson, Tatiana A; Dyhrman, Sonya T

2015-04-28

Diverse communities of marine phytoplankton carry out half of global primary production. The vast diversity of the phytoplankton has long perplexed ecologists because these organisms coexist in an isotropic environment while competing for the same basic resources (e.g., inorganic nutrients). Differential niche partitioning of resources is one hypothesis to explain this "paradox of the plankton," but it is difficult to quantify and track variation in phytoplankton metabolism in situ. Here, we use quantitative metatranscriptome analyses to examine pathways of nitrogen (N) and phosphorus (P) metabolism in diatoms that cooccur regularly in an estuary on the east coast of the United States (Narragansett Bay). Expression of known N and P metabolic pathways varied between diatoms, indicating apparent differences in resource utilization capacity that may prevent direct competition. Nutrient amendment incubations skewed N/P ratios, elucidating nutrient-responsive patterns of expression and facilitating a quantitative comparison between diatoms. The resource-responsive (RR) gene sets deviated in composition from the metabolic profile of the organism, being enriched in genes associated with N and P metabolism. Expression of the RR gene set varied over time and differed significantly between diatoms, resulting in opposite transcriptional responses to the same environment. Apparent differences in metabolic capacity and the expression of that capacity in the environment suggest that diatom-specific resource partitioning was occurring in Narragansett Bay. This high-resolution approach highlights the molecular underpinnings of diatom resource utilization and how cooccurring diatoms adjust their cellular physiology to partition their niche space.

Combined clinical and home rehabilitation: case report of an integrated knowledge-to-action study in a Dutch rehabilitation stroke unit.

PubMed

Nanninga, Christa S; Postema, Klaas; Schönherr, Marleen C; van Twillert, Sacha; Lettinga, Ant T

2015-04-01

There is growing awareness that the poor uptake of evidence in health care is not a knowledge-transfer problem but rather one of knowledge production. This issue calls for re-examination of the evidence produced and assumptions that underpin existing knowledge-to-action (KTA) activities. Accordingly, it has been advocated that KTA studies should treat research knowledge and local practical knowledge with analytical impartiality. The purpose of this case report is to illustrate the complexities in an evidence-informed improvement process of organized stroke care in a local rehabilitation setting. A participatory action approach was used to co-create knowledge and engage local therapists in a 2-way knowledge translation and multidirectional learning process. Evidence regarding rehabilitation stroke units was applied in a straightforward manner, as the setting met the criteria articulated in stroke unit reviews. Evidence on early supported discharge (ESD) could not be directly applied because of differences in target group and implementation environment between the local and reviewed settings. Early supported discharge was tailored to the needs of patients severely affected by stroke admitted to the local rehabilitation stroke unit by combining clinical and home rehabilitation (CCHR). Local therapists welcomed CCHR because it helped them make their task-specific training truly context specific. Key barriers to implementation were travel time, logistical problems, partitioning walls between financing streams, and legislative procedures. Improving local settings with available evidence is not a straightforward application process but rather a matter of searching, logical reasoning, and creatively working with heterogeneous knowledge sources in partnership with different stakeholders. Multiple organizational levels need to be addressed rather than focusing on therapists as sole site of change. © 2015 American Physical Therapy Association.

Parallel fast multipole boundary element method applied to computational homogenization

NASA Astrophysics Data System (ADS)

Ptaszny, Jacek

2018-01-01

In the present work, a fast multipole boundary element method (FMBEM) and a parallel computer code for 3D elasticity problem is developed and applied to the computational homogenization of a solid containing spherical voids. The system of equation is solved by using the GMRES iterative solver. The boundary of the body is dicretized by using the quadrilateral serendipity elements with an adaptive numerical integration. Operations related to a single GMRES iteration, performed by traversing the corresponding tree structure upwards and downwards, are parallelized by using the OpenMP standard. The assignment of tasks to threads is based on the assumption that the tree nodes at which the moment transformations are initialized can be partitioned into disjoint sets of equal or approximately equal size and assigned to the threads. The achieved speedup as a function of number of threads is examined.

Aggregation models on hypergraphs

NASA Astrophysics Data System (ADS)

Alberici, Diego; Contucci, Pierluigi; Mingione, Emanuele; Molari, Marco

2017-01-01

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer-dimer case. After translating those relations into structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.

A new weak Galerkin finite element method for elliptic interface problems

DOE PAGES

Mu, Lin; Wang, Junping; Ye, Xiu; ...

2016-08-26

We introduce and analyze a new weak Galerkin (WG) finite element method in this paper for solving second order elliptic equations with discontinuous coefficients and interfaces. Comparing with the existing WG algorithm for solving the same type problems, the present WG method has a simpler variational formulation and fewer unknowns. Moreover, the new WG algorithm allows the use of finite element partitions consisting of general polytopal meshes and can be easily generalized to high orders. Optimal order error estimates in both H1 and L2 norms are established for the present WG finite element solutions. We conducted extensive numerical experiments inmore » order to examine the accuracy, flexibility, and robustness of the proposed WG interface approach. In solving regular elliptic interface problems, high order convergences are numerically confirmed by using piecewise polynomial basis functions of high degrees. Moreover, the WG method is shown to be able to accommodate very complicated interfaces, due to its flexibility in choosing finite element partitions. Finally, in dealing with challenging problems with low regularities, the piecewise linear WG method is capable of delivering a second order of accuracy in L∞ norm for both C1 and H2 continuous solutions.« less

A new weak Galerkin finite element method for elliptic interface problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Lin; Wang, Junping; Ye, Xiu

We introduce and analyze a new weak Galerkin (WG) finite element method in this paper for solving second order elliptic equations with discontinuous coefficients and interfaces. Comparing with the existing WG algorithm for solving the same type problems, the present WG method has a simpler variational formulation and fewer unknowns. Moreover, the new WG algorithm allows the use of finite element partitions consisting of general polytopal meshes and can be easily generalized to high orders. Optimal order error estimates in both H1 and L2 norms are established for the present WG finite element solutions. We conducted extensive numerical experiments inmore » order to examine the accuracy, flexibility, and robustness of the proposed WG interface approach. In solving regular elliptic interface problems, high order convergences are numerically confirmed by using piecewise polynomial basis functions of high degrees. Moreover, the WG method is shown to be able to accommodate very complicated interfaces, due to its flexibility in choosing finite element partitions. Finally, in dealing with challenging problems with low regularities, the piecewise linear WG method is capable of delivering a second order of accuracy in L∞ norm for both C1 and H2 continuous solutions.« less

Probing quantum state space: does one have to learn everything to learn something?

PubMed

Carmeli, Claudio; Heinosaari, Teiko; Schultz, Jussi; Toigo, Alessandro

2017-05-01

Determining the state of a quantum system is a consuming procedure. For this reason, whenever one is interested only in some particular property of a state, it would be desirable to design a measurement set-up that reveals this property with as little effort as possible. Here, we investigate whether, in order to successfully complete a given task of this kind, one needs an informationally complete measurement, or if something less demanding would suffice. The first alternative means that in order to complete the task, one needs a measurement which fully determines the state. We formulate the task as a membership problem related to a partitioning of the quantum state space and, in doing so, connect it to the geometry of the state space. For a general membership problem, we prove various sufficient criteria that force informational completeness, and we explicitly treat several physically relevant examples. For the specific cases that do not require informational completeness, we also determine bounds on the minimal number of measurement outcomes needed to ensure success in the task.

Probing quantum state space: does one have to learn everything to learn something?

PubMed Central

Carmeli, Claudio; Schultz, Jussi; Toigo, Alessandro

2017-01-01

Determining the state of a quantum system is a consuming procedure. For this reason, whenever one is interested only in some particular property of a state, it would be desirable to design a measurement set-up that reveals this property with as little effort as possible. Here, we investigate whether, in order to successfully complete a given task of this kind, one needs an informationally complete measurement, or if something less demanding would suffice. The first alternative means that in order to complete the task, one needs a measurement which fully determines the state. We formulate the task as a membership problem related to a partitioning of the quantum state space and, in doing so, connect it to the geometry of the state space. For a general membership problem, we prove various sufficient criteria that force informational completeness, and we explicitly treat several physically relevant examples. For the specific cases that do not require informational completeness, we also determine bounds on the minimal number of measurement outcomes needed to ensure success in the task. PMID:28588404

A Least-Squares-Based Weak Galerkin Finite Element Method for Second Order Elliptic Equations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mu, Lin; Wang, Junping; Ye, Xiu

Here, in this article, we introduce a least-squares-based weak Galerkin finite element method for the second order elliptic equation. This new method is shown to provide very accurate numerical approximations for both the primal and the flux variables. In contrast to other existing least-squares finite element methods, this new method allows us to use discontinuous approximating functions on finite element partitions consisting of arbitrary polygon/polyhedron shapes. We also develop a Schur complement algorithm for the resulting discretization problem by eliminating all the unknowns that represent the solution information in the interior of each element. Optimal order error estimates for bothmore » the primal and the flux variables are established. An extensive set of numerical experiments are conducted to demonstrate the robustness, reliability, flexibility, and accuracy of the least-squares-based weak Galerkin finite element method. Finally, the numerical examples cover a wide range of applied problems, including singularly perturbed reaction-diffusion equations and the flow of fluid in porous media with strong anisotropy and heterogeneity.« less

A Least-Squares-Based Weak Galerkin Finite Element Method for Second Order Elliptic Equations

DOE PAGES

Mu, Lin; Wang, Junping; Ye, Xiu

2017-08-17

Here, in this article, we introduce a least-squares-based weak Galerkin finite element method for the second order elliptic equation. This new method is shown to provide very accurate numerical approximations for both the primal and the flux variables. In contrast to other existing least-squares finite element methods, this new method allows us to use discontinuous approximating functions on finite element partitions consisting of arbitrary polygon/polyhedron shapes. We also develop a Schur complement algorithm for the resulting discretization problem by eliminating all the unknowns that represent the solution information in the interior of each element. Optimal order error estimates for bothmore » the primal and the flux variables are established. An extensive set of numerical experiments are conducted to demonstrate the robustness, reliability, flexibility, and accuracy of the least-squares-based weak Galerkin finite element method. Finally, the numerical examples cover a wide range of applied problems, including singularly perturbed reaction-diffusion equations and the flow of fluid in porous media with strong anisotropy and heterogeneity.« less

Superpixel Cut for Figure-Ground Image Segmentation

NASA Astrophysics Data System (ADS)

Yang, Michael Ying; Rosenhahn, Bodo

2016-06-01

Figure-ground image segmentation has been a challenging problem in computer vision. Apart from the difficulties in establishing an effective framework to divide the image pixels into meaningful groups, the notions of figure and ground often need to be properly defined by providing either user inputs or object models. In this paper, we propose a novel graph-based segmentation framework, called superpixel cut. The key idea is to formulate foreground segmentation as finding a subset of superpixels that partitions a graph over superpixels. The problem is formulated as Min-Cut. Therefore, we propose a novel cost function that simultaneously minimizes the inter-class similarity while maximizing the intra-class similarity. This cost function is optimized using parametric programming. After a small learning step, our approach is fully automatic and fully bottom-up, which requires no high-level knowledge such as shape priors and scene content. It recovers coherent components of images, providing a set of multiscale hypotheses for high-level reasoning. We evaluate our proposed framework by comparing it to other generic figure-ground segmentation approaches. Our method achieves improved performance on state-of-the-art benchmark databases.

The partitioning of heavy metals in incineration of sludges and waste in a bubbling fluidized bed 2. Interpretation of results with a conceptual model.

PubMed

Toledo, José M; Corella, José; Corella, Luis M

2005-11-11

This work addresses the behavior, fate and/or partitioning of six targeted (Cd, Pb, Cr, Cu, Zn and Ni) heavy metals (HMs) in the incineration of sludges and waste in a bubbling fluidized bed (BFB) of 15 cm i.d. and 5.2m high followed by a filter chamber operated at 750-760 degrees C with a commercial ceramic filter. This paper presents three different things: (1) an in depth review of the published work relating to the problem of partitioning of the HMs in BFBs, (2) some more experimental incineration tests regarding the influence of the temperature of the bed of the BFB and the effect of the chlorine content in the feedstock on the partitioning of the HMs, and (3) the modelling of the partitioning of the HMs in the exit flows: bottom ash, coarse fly ashes, fine fly ash and vapour phase. The partitioning of the HMs is governed by fluid dynamic principles together with the kinetics of the diffusion of the HMs inside the ash particles and the kinetics of the reactions between the HMs and the components of the matrix of the ash. Some thermodynamic predictions do not fit the results from the BFB incinerator well enough because equilibria are not reached in at least three exit ash flows: coarse fly ash, fine fly ash and submicron particles. The residence time of these ash particles in these type of incinerators is very short and most of the HMs have no time to diffuse out of the ash particle. Finally, an examination was made on how in the ceramic hot filter the partition coefficients for the HMs increased, mainly for Cd and Pb, when the Cl-content in the feedstock was increased.

Weights and topology: a study of the effects of graph construction on 3D image segmentation.

PubMed

Grady, Leo; Jolly, Marie-Pierre

2008-01-01

Graph-based algorithms have become increasingly popular for medical image segmentation. The fundamental process for each of these algorithms is to use the image content to generate a set of weights for the graph and then set conditions for an optimal partition of the graph with respect to these weights. To date, the heuristics used for generating the weighted graphs from image intensities have largely been ignored, while the primary focus of attention has been on the details of providing the partitioning conditions. In this paper we empirically study the effects of graph connectivity and weighting function on the quality of the segmentation results. To control for algorithm-specific effects, we employ both the Graph Cuts and Random Walker algorithms in our experiments.

Tuning collective communication for Partitioned Global Address Space programming models

DOE PAGES

Nishtala, Rajesh; Zheng, Yili; Hargrove, Paul H.; ...

2011-06-12

Partitioned Global Address Space (PGAS) languages offer programmers the convenience of a shared memory programming style combined with locality control necessary to run on large-scale distributed memory systems. Even within a PGAS language programmers often need to perform global communication operations such as broadcasts or reductions, which are best performed as collective operations in which a group of threads work together to perform the operation. In this study we consider the problem of implementing collective communication within PGAS languages and explore some of the design trade-offs in both the interface and implementation. In particular, PGAS collectives have semantic issues thatmore » are different than in send–receive style message passing programs, and different implementation approaches that take advantage of the one-sided communication style in these languages. We present an implementation framework for PGAS collectives as part of the GASNet communication layer, which supports shared memory, distributed memory and hybrids. The framework supports a broad set of algorithms for each collective, over which the implementation may be automatically tuned. In conclusion, we demonstrate the benefit of optimized GASNet collectives using application benchmarks written in UPC, and demonstrate that the GASNet collectives can deliver scalable performance on a variety of state-of-the-art parallel machines including a Cray XT4, an IBM BlueGene/P, and a Sun Constellation system with InfiniBand interconnect.« less

A discrete scattering series representation for lattice embedded models of chain cyclization

NASA Astrophysics Data System (ADS)

Fraser, Simon J.; Winnik, Mitchell A.

1980-01-01

In this paper we develop a lattice based model of chain cyclization in the presence of a set of occupied sites V in the lattice. We show that within the approximation of a Markovian chain propagator the effect of V on the partition function for the system can be written as a time-ordered exponential series in which V behaves like a scattering potential and chainlength is the timelike parameter. The discrete and finite nature of this model allows us to obtain rigorous upper and lower bounds to the series limit. We adapt these formulas to calculation of the partition functions and cyclization probabilities of terminally and globally cyclizing chains. Two classes of cyclization are considered: in the first model the target set H may be visited repeatedly (the Markovian model); in the second case vertices in H may be visited at most once(the non-Markovian or taboo model). This formulation depends on two fundamental combinatorial structures, namely the inclusion-exclusion principle and the set of subsets of a set. We have tried to interpret these abstract structures with physical analogies throughout the paper.

Fragment-based prediction of skin sensitization using recursive partitioning

NASA Astrophysics Data System (ADS)

Lu, Jing; Zheng, Mingyue; Wang, Yong; Shen, Qiancheng; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian

2011-09-01

Skin sensitization is an important toxic endpoint in the risk assessment of chemicals. In this paper, structure-activity relationships analysis was performed on the skin sensitization potential of 357 compounds with local lymph node assay data. Structural fragments were extracted by GASTON (GrAph/Sequence/Tree extractiON) from the training set. Eight fragments with accuracy significantly higher than 0.73 ( p < 0.1) were retained to make up an indicator descriptor fragment. The fragment descriptor and eight other physicochemical descriptors closely related to the endpoint were calculated to construct the recursive partitioning tree (RP tree) for classification. The balanced accuracy of the training set, test set I, and test set II in the leave-one-out model were 0.846, 0.800, and 0.809, respectively. The results highlight that fragment-based RP tree is a preferable method for identifying skin sensitizers. Moreover, the selected fragments provide useful structural information for exploring sensitization mechanisms, and RP tree creates a graphic tree to identify the most important properties associated with skin sensitization. They can provide some guidance for designing of drugs with lower sensitization level.

A knowledge based system for scientific data visualization

NASA Technical Reports Server (NTRS)

Senay, Hikmet; Ignatius, Eve

1992-01-01

A knowledge-based system, called visualization tool assistant (VISTA), which was developed to assist scientists in the design of scientific data visualization techniques, is described. The system derives its knowledge from several sources which provide information about data characteristics, visualization primitives, and effective visual perception. The design methodology employed by the system is based on a sequence of transformations which decomposes a data set into a set of data partitions, maps this set of partitions to visualization primitives, and combines these primitives into a composite visualization technique design. Although the primary function of the system is to generate an effective visualization technique design for a given data set by using principles of visual perception the system also allows users to interactively modify the design, and renders the resulting image using a variety of rendering algorithms. The current version of the system primarily supports visualization techniques having applicability in earth and space sciences, although it may easily be extended to include other techniques useful in other disciplines such as computational fluid dynamics, finite-element analysis and medical imaging.

The design and research of anti-color-noise chaos M-ary communication system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fu, Yongqing, E-mail: fuyongqing@hrbeu.edu.cn; Li, Xingyuan; Li, Yanan

Previously a novel chaos M-ary digital communication method based on spatiotemporal chaos Hamilton oscillator has been proposed. Without chaos synchronization circumstance, it has performance improvement in bandwidth efficiency, transmission efficiency and anti-white-noise performance compared with traditional communication method. In this paper, the channel noise influence on chaotic modulation signals and the construction problem of anti-color-noise chaotic M-ary communication system are studied. The formula of zone partition demodulator’s boundary in additive white Gaussian noise is derived, besides, the problem about how to determine the boundary of zone partition demodulator in additive color noise is deeply studied; Then an approach on constructingmore » anti-color-noise chaos M-ary communication system is proposed, in which a pre-distortion filter is added after the chaos baseband modulator in the transmitter and whitening filter is added before zone partition demodulator in the receiver. Finally, the chaos M-ary communication system based on Hamilton oscillator is constructed and simulated in different channel noise. The result shows that the proposed method in this paper can improve the anti-color-noise performance of the whole communication system compared with the former system, and it has better anti-fading and resisting disturbance performance than Quadrature Phase Shift Keying system.« less

Analytical results for a stochastic model of gene expression with arbitrary partitioning of proteins

NASA Astrophysics Data System (ADS)

Tschirhart, Hugo; Platini, Thierry

2018-05-01

In biophysics, the search for analytical solutions of stochastic models of cellular processes is often a challenging task. In recent work on models of gene expression, it was shown that a mapping based on partitioning of Poisson arrivals (PPA-mapping) can lead to exact solutions for previously unsolved problems. While the approach can be used in general when the model involves Poisson processes corresponding to creation or degradation, current applications of the method and new results derived using it have been limited to date. In this paper, we present the exact solution of a variation of the two-stage model of gene expression (with time dependent transition rates) describing the arbitrary partitioning of proteins. The methodology proposed makes full use of the PPA-mapping by transforming the original problem into a new process describing the evolution of three biological switches. Based on a succession of transformations, the method leads to a hierarchy of reduced models. We give an integral expression of the time dependent generating function as well as explicit results for the mean, variance, and correlation function. Finally, we discuss how results for time dependent parameters can be extended to the three-stage model and used to make inferences about models with parameter fluctuations induced by hidden stochastic variables.

Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection.

PubMed

Wang, Huiya; Feng, Jun; Wang, Hongyu

2017-07-20

Detection of clustered microcalcification (MC) from mammograms plays essential roles in computer-aided diagnosis for early stage breast cancer. To tackle problems associated with the diversity of data structures of MC lesions and the variability of normal breast tissues, multi-pattern sample space learning is required. In this paper, a novel grouped fuzzy Support Vector Machine (SVM) algorithm with sample space partition based on Expectation-Maximization (EM) (called G-FSVM) is proposed for clustered MC detection. The diversified pattern of training data is partitioned into several groups based on EM algorithm. Then a series of fuzzy SVM are integrated for classification with each group of samples from the MC lesions and normal breast tissues. From DDSM database, a total of 1,064 suspicious regions are selected from 239 mammography, and the measurement of Accuracy, True Positive Rate (TPR), False Positive Rate (FPR) and EVL = TPR* 1-FPR are 0.82, 0.78, 0.14 and 0.72, respectively. The proposed method incorporates the merits of fuzzy SVM and multi-pattern sample space learning, decomposing the MC detection problem into serial simple two-class classification. Experimental results from synthetic data and DDSM database demonstrate that our integrated classification framework reduces the false positive rate significantly while maintaining the true positive rate.

Efficient Deterministic Finite Automata Minimization Based on Backward Depth Information

PubMed Central

Liu, Desheng; Huang, Zhiping; Zhang, Yimeng; Guo, Xiaojun; Su, Shaojing

2016-01-01

Obtaining a minimal automaton is a fundamental issue in the theory and practical implementation of deterministic finite automatons (DFAs). A minimization algorithm is presented in this paper that consists of two main phases. In the first phase, the backward depth information is built, and the state set of the DFA is partitioned into many blocks. In the second phase, the state set is refined using a hash table. The minimization algorithm has a lower time complexity O(n) than a naive comparison of transitions O(n2). Few states need to be refined by the hash table, because most states have been partitioned by the backward depth information in the coarse partition. This method achieves greater generality than previous methods because building the backward depth information is independent of the topological complexity of the DFA. The proposed algorithm can be applied not only to the minimization of acyclic automata or simple cyclic automata, but also to automata with high topological complexity. Overall, the proposal has three advantages: lower time complexity, greater generality, and scalability. A comparison to Hopcroft’s algorithm demonstrates experimentally that the algorithm runs faster than traditional algorithms. PMID:27806102

Partition resampling and extrapolation averaging: approximation methods for quantifying gene expression in large numbers of short oligonucleotide arrays.

PubMed

Goldstein, Darlene R

2006-10-01

Studies of gene expression using high-density short oligonucleotide arrays have become a standard in a variety of biological contexts. Of the expression measures that have been proposed to quantify expression in these arrays, multi-chip-based measures have been shown to perform well. As gene expression studies increase in size, however, utilizing multi-chip expression measures is more challenging in terms of computing memory requirements and time. A strategic alternative to exact multi-chip quantification on a full large chip set is to approximate expression values based on subsets of chips. This paper introduces an extrapolation method, Extrapolation Averaging (EA), and a resampling method, Partition Resampling (PR), to approximate expression in large studies. An examination of properties indicates that subset-based methods can perform well compared with exact expression quantification. The focus is on short oligonucleotide chips, but the same ideas apply equally well to any array type for which expression is quantified using an entire set of arrays, rather than for only a single array at a time. Software implementing Partition Resampling and Extrapolation Averaging is under development as an R package for the BioConductor project.

Exact calculation of loop formation probability identifies folding motifs in RNA secondary structures

PubMed Central

Sloma, Michael F.; Mathews, David H.

2016-01-01

RNA secondary structure prediction is widely used to analyze RNA sequences. In an RNA partition function calculation, free energy nearest neighbor parameters are used in a dynamic programming algorithm to estimate statistical properties of the secondary structure ensemble. Previously, partition functions have largely been used to estimate the probability that a given pair of nucleotides form a base pair, the conditional stacking probability, the accessibility to binding of a continuous stretch of nucleotides, or a representative sample of RNA structures. Here it is demonstrated that an RNA partition function can also be used to calculate the exact probability of formation of hairpin loops, internal loops, bulge loops, or multibranch loops at a given position. This calculation can also be used to estimate the probability of formation of specific helices. Benchmarking on a set of RNA sequences with known secondary structures indicated that loops that were calculated to be more probable were more likely to be present in the known structure than less probable loops. Furthermore, highly probable loops are more likely to be in the known structure than the set of loops predicted in the lowest free energy structures. PMID:27852924

Distributed memory compiler methods for irregular problems: Data copy reuse and runtime partitioning

NASA Technical Reports Server (NTRS)

Das, Raja; Ponnusamy, Ravi; Saltz, Joel; Mavriplis, Dimitri

1991-01-01

Outlined here are two methods which we believe will play an important role in any distributed memory compiler able to handle sparse and unstructured problems. We describe how to link runtime partitioners to distributed memory compilers. In our scheme, programmers can implicitly specify how data and loop iterations are to be distributed between processors. This insulates users from having to deal explicitly with potentially complex algorithms that carry out work and data partitioning. We also describe a viable mechanism for tracking and reusing copies of off-processor data. In many programs, several loops access the same off-processor memory locations. As long as it can be verified that the values assigned to off-processor memory locations remain unmodified, we show that we can effectively reuse stored off-processor data. We present experimental data from a 3-D unstructured Euler solver run on iPSC/860 to demonstrate the usefulness of our methods.

Metal-silicate thermochemistry at high temperature - Magma oceans and the 'excess siderophile element' problem of the earth's upper mantle

NASA Technical Reports Server (NTRS)

Capobianco, Christopher J.; Jones, John H.; Drake, Michael J.

1993-01-01

Low-temperature metal-silicate partition coefficients are extrapolated to magma ocean temperatures. If the low-temperature chemistry data is found to be applicable at high temperatures, an important assumption, then the results indicate that high temperature alone cannot account for the excess siderophile element problem of the upper mantle. For most elements, a rise in temperature will result in a modest increase in siderophile behavior if an iron-wuestite redox buffer is paralleled. However, long-range extrapolation of experimental data is hazardous when the data contains even modest experimental errors. For a given element, extrapolated high-temperature partition coefficients can differ by orders of magnitude, even when data from independent studies is consistent within quoted errors. In order to accurately assess siderophile element behavior in a magma ocean, it will be necessary to obtain direct experimental measurements for at least some of the siderophile elements.

Value-based customer grouping from large retail data sets

NASA Astrophysics Data System (ADS)

Strehl, Alexander; Ghosh, Joydeep

2000-04-01

In this paper, we propose OPOSSUM, a novel similarity-based clustering algorithm using constrained, weighted graph- partitioning. Instead of binary presence or absence of products in a market-basket, we use an extended 'revenue per product' measure to better account for management objectives. Typically the number of clusters desired in a database marketing application is only in the teens or less. OPOSSUM proceeds top-down, which is more efficient and takes a small number of steps to attain the desired number of clusters as compared to bottom-up agglomerative clustering approaches. OPOSSUM delivers clusters that are balanced in terms of either customers (samples) or revenue (value). To facilitate data exploration and validation of results we introduce CLUSION, a visualization toolkit for high-dimensional clustering problems. To enable closed loop deployment of the algorithm, OPOSSUM has no user-specified parameters. Thresholding heuristics are avoided and the optimal number of clusters is automatically determined by a search for maximum performance. Results are presented on a real retail industry data-set of several thousand customers and products, to demonstrate the power of the proposed technique.

Solving Autonomy Technology Gaps through Wireless Technology and Orion Avionics Architectural Principles

NASA Astrophysics Data System (ADS)

Black, Randy; Bai, Haowei; Michalicek, Andrew; Shelton, Blaine; Villela, Mark

2008-01-01

Currently, autonomy in space applications is limited by a variety of technology gaps. Innovative application of wireless technology and avionics architectural principles drawn from the Orion crew exploration vehicle provide solutions for several of these gaps. The Vision for Space Exploration envisions extensive use of autonomous systems. Economic realities preclude continuing the level of operator support currently required of autonomous systems in space. In order to decrease the number of operators, more autonomy must be afforded to automated systems. However, certification authorities have been notoriously reluctant to certify autonomous software in the presence of humans or when costly missions may be jeopardized. The Orion avionics architecture, drawn from advanced commercial aircraft avionics, is based upon several architectural principles including partitioning in software. Robust software partitioning provides "brick wall" separation between software applications executing on a single processor, along with controlled data movement between applications. Taking advantage of these attributes, non-deterministic applications can be placed in one partition and a "Safety" application created in a separate partition. This "Safety" partition can track the position of astronauts or critical equipment and prevent any unsafe command from executing. Only the Safety partition need be certified to a human rated level. As a proof-of-concept demonstration, Honeywell has teamed with the Ultra WideBand (UWB) Working Group at NASA Johnson Space Center to provide tracking of humans, autonomous systems, and critical equipment. Using UWB the NASA team can determine positioning to within less than one inch resolution, allowing a Safety partition to halt operation of autonomous systems in the event that an unplanned collision is imminent. Another challenge facing autonomous systems is the coordination of multiple autonomous agents. Current approaches address the issue as one of networking and coordination of multiple independent units, each with its own mission. As a proof-of-concept Honeywell is developing and testing various algorithms that lead to a deterministic, fault tolerant, reliable wireless backplane. Just as advanced avionics systems control several subsystems, actuators, sensors, displays, etc.; a single "master" autonomous agent (or base station computer) could control multiple autonomous systems. The problem is simplified to controlling a flexible body consisting of several sensors and actuators, rather than one of coordinating multiple independent units. By filling technology gaps associated with space based autonomous system, wireless technology and Orion architectural principles provide the means for decreasing operational costs and simplifying problems associated with collaboration of multiple autonomous systems.

Epidemic Reconstruction in a Phylogenetics Framework: Transmission Trees as Partitions of the Node Set

PubMed Central

Hall, Matthew; Woolhouse, Mark; Rambaut, Andrew

2015-01-01

The use of genetic data to reconstruct the transmission tree of infectious disease epidemics and outbreaks has been the subject of an increasing number of studies, but previous approaches have usually either made assumptions that are not fully compatible with phylogenetic inference, or, where they have based inference on a phylogeny, have employed a procedure that requires this tree to be fixed. At the same time, the coalescent-based models of the pathogen population that are employed in the methods usually used for time-resolved phylogeny reconstruction are a considerable simplification of epidemic process, as they assume that pathogen lineages mix freely. Here, we contribute a new method that is simultaneously a phylogeny reconstruction method for isolates taken from an epidemic, and a procedure for transmission tree reconstruction. We observe that, if one or more samples is taken from each host in an epidemic or outbreak and these are used to build a phylogeny, a transmission tree is equivalent to a partition of the set of nodes of this phylogeny, such that each partition element is a set of nodes that is connected in the full tree and contains all the tips corresponding to samples taken from one and only one host. We then implement a Monte Carlo Markov Chain (MCMC) procedure for simultaneous sampling from the spaces of both trees, utilising a newly-designed set of phylogenetic tree proposals that also respect node partitions. We calculate the posterior probability of these partitioned trees based on a model that acknowledges the population structure of an epidemic by employing an individual-based disease transmission model and a coalescent process taking place within each host. We demonstrate our method, first using simulated data, and then with sequences taken from the H7N7 avian influenza outbreak that occurred in the Netherlands in 2003. We show that it is superior to established coalescent methods for reconstructing the topology and node heights of the phylogeny and performs well for transmission tree reconstruction when the phylogeny is well-resolved by the genetic data, but caution that this will often not be the case in practice and that existing genetic and epidemiological data should be used to configure such analyses whenever possible. This method is available for use by the research community as part of BEAST, one of the most widely-used packages for reconstruction of dated phylogenies. PMID:26717515

Community detection in complex networks by using membrane algorithm

NASA Astrophysics Data System (ADS)

Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren

Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.

Experiments to Distribute Map Generalization Processes

NASA Astrophysics Data System (ADS)

Berli, Justin; Touya, Guillaume; Lokhat, Imran; Regnauld, Nicolas

2018-05-01

Automatic map generalization requires the use of computationally intensive processes often unable to deal with large datasets. Distributing the generalization process is the only way to make them scalable and usable in practice. But map generalization is a highly contextual process, and the surroundings of a generalized map feature needs to be known to generalize the feature, which is a problem as distribution might partition the dataset and parallelize the processing of each part. This paper proposes experiments to evaluate the past propositions to distribute map generalization, and to identify the main remaining issues. The past propositions to distribute map generalization are first discussed, and then the experiment hypotheses and apparatus are described. The experiments confirmed that regular partitioning was the quickest strategy, but also the less effective in taking context into account. The geographical partitioning, though less effective for now, is quite promising regarding the quality of the results as it better integrates the geographical context.

Research in interactive scene analysis

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M.; Garvey, T. D.; Weyl, S. A.; Wolf, H. C.

1975-01-01

An interactive scene interpretation system (ISIS) was developed as a tool for constructing and experimenting with man-machine and automatic scene analysis methods tailored for particular image domains. A recently developed region analysis subsystem based on the paradigm of Brice and Fennema is described. Using this subsystem a series of experiments was conducted to determine good criteria for initially partitioning a scene into atomic regions and for merging these regions into a final partition of the scene along object boundaries. Semantic (problem-dependent) knowledge is essential for complete, correct partitions of complex real-world scenes. An interactive approach to semantic scene segmentation was developed and demonstrated on both landscape and indoor scenes. This approach provides a reasonable methodology for segmenting scenes that cannot be processed completely automatically, and is a promising basis for a future automatic system. A program is described that can automatically generate strategies for finding specific objects in a scene based on manually designated pictorial examples.

Setting objective thresholds for rare event detection in flow cytometry

PubMed Central

Richards, Adam J.; Staats, Janet; Enzor, Jennifer; McKinnon, Katherine; Frelinger, Jacob; Denny, Thomas N.; Weinhold, Kent J.; Chan, Cliburn

2014-01-01

The accurate identification of rare antigen-specific cytokine positive cells from peripheral blood mononuclear cells (PBMC) after antigenic stimulation in an intracellular staining (ICS) flow cytometry assay is challenging, as cytokine positive events may be fairly diffusely distributed and lack an obvious separation from the negative population. Traditionally, the approach by flow operators has been to manually set a positivity threshold to partition events into cytokine-positive and cytokine-negative. This approach suffers from subjectivity and inconsistency across different flow operators. The use of statistical clustering methods does not remove the need to find an objective threshold between between positive and negative events since consistent identification of rare event subsets is highly challenging for automated algorithms, especially when there is distributional overlap between the positive and negative events (“smear”). We present a new approach, based on the Fβ measure, that is similar to manual thresholding in providing a hard cutoff, but has the advantage of being determined objectively. The performance of this algorithm is compared with results obtained by expert visual gating. Several ICS data sets from the External Quality Assurance Program Oversight Laboratory (EQAPOL) proficiency program were used to make the comparisons. We first show that visually determined thresholds are difficult to reproduce and pose a problem when comparing results across operators or laboratories, as well as problems that occur with the use of commonly employed clustering algorithms. In contrast, a single parameterization for the Fβ method performs consistently across different centers, samples, and instruments because it optimizes the precision/recall tradeoff by using both negative and positive controls. PMID:24727143

On delay adjustment for dynamic load balancing in distributed virtual environments.

PubMed

Deng, Yunhua; Lau, Rynson W H

2012-04-01

Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead.

Hierarchical Solution of the Traveling Salesman Problem with Random Dyadic Tilings

NASA Astrophysics Data System (ADS)

Kalmár-Nagy, Tamás; Bak, Bendegúz Dezső

We propose a hierarchical heuristic approach for solving the Traveling Salesman Problem (TSP) in the unit square. The points are partitioned with a random dyadic tiling and clusters are formed by the points located in the same tile. Each cluster is represented by its geometrical barycenter and a “coarse” TSP solution is calculated for these barycenters. Midpoints are placed at the middle of each edge in the coarse solution. Near-optimal (or optimal) minimum tours are computed for each cluster. The tours are concatenated using the midpoints yielding a solution for the original TSP. The method is tested on random TSPs (independent, identically distributed points in the unit square) up to 10,000 points as well as on a popular benchmark problem (att532 — coordinates of 532 American cities). Our solutions are 8-13% longer than the optimal ones. We also present an optimization algorithm for the partitioning to improve our solutions. This algorithm further reduces the solution errors (by several percent using 1000 iteration steps). The numerical experiments demonstrate the viability of the approach.

Modeling homeorhetic trajectories of milk component yields, body composition and dry-matter intake in dairy cows: Influence of parity, milk production potential and breed.

PubMed

Daniel, J B; Friggens, N C; van Laar, H; Ingvartsen, K L; Sauvant, D

2018-06-01

The control of nutrient partitioning is complex and affected by many factors, among them physiological state and production potential. Therefore, the current model aims to provide for dairy cows a dynamic framework to predict a consistent set of reference performance patterns (milk component yields, body composition change, dry-matter intake) sensitive to physiological status across a range of milk production potentials (within and between breeds). Flows and partition of net energy toward maintenance, growth, gestation, body reserves and milk components are described in the model. The structure of the model is characterized by two sub-models, a regulating sub-model of homeorhetic control which sets dynamic partitioning rules along the lactation, and an operating sub-model that translates this into animal performance. The regulating sub-model describes lactation as the result of three driving forces: (1) use of previously acquired resources through mobilization, (2) acquisition of new resources with a priority of partition towards milk and (3) subsequent use of resources towards body reserves gain. The dynamics of these three driving forces were adjusted separately for fat (milk and body), protein (milk and body) and lactose (milk). Milk yield is predicted from lactose and protein yields with an empirical equation developed from literature data. The model predicts desired dry-matter intake as an outcome of net energy requirements for a given dietary net energy content. The parameters controlling milk component yields and body composition changes were calibrated using two data sets in which the diet was the same for all animals. Weekly data from Holstein dairy cows was used to calibrate the model within-breed across milk production potentials. A second data set was used to evaluate the model and to calibrate it for breed differences (Holstein, Danish Red and Jersey) on the mobilization/reconstitution of body composition and on the yield of individual milk components. These calibrations showed that the model framework was able to adequately simulate milk yield, milk component yields, body composition changes and dry-matter intake throughout lactation for primiparous and multiparous cows differing in their production level.

A stable partitioned FSI algorithm for rigid bodies and incompressible flow. Part I: Model problem analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Banks, J. W.; Henshaw, W. D.; Schwendeman, D. W.

A stable partitioned algorithm is developed for fluid-structure interaction (FSI) problems involving viscous incompressible flow and rigid bodies. This added-mass partitioned (AMP) algorithm remains stable, without sub-iterations, for light and even zero mass rigid bodies when added-mass and viscous added-damping effects are large. The scheme is based on a generalized Robin interface condition for the fluid pressure that includes terms involving the linear acceleration and angular acceleration of the rigid body. Added mass effects are handled in the Robin condition by inclusion of a boundary integral term that depends on the pressure. Added-damping effects due to the viscous shear forcesmore » on the body are treated by inclusion of added-damping tensors that are derived through a linearization of the integrals defining the force and torque. Added-damping effects may be important at low Reynolds number, or, for example, in the case of a rotating cylinder or rotating sphere when the rotational moments of inertia are small. In this second part of a two-part series, the general formulation of the AMP scheme is presented including the form of the AMP interface conditions and added-damping tensors for general geometries. A fully second-order accurate implementation of the AMP scheme is developed in two dimensions based on a fractional-step method for the incompressible Navier-Stokes equations using finite difference methods and overlapping grids to handle the moving geometry. Here, the numerical scheme is verified on a number of difficult benchmark problems.« less

A stable partitioned FSI algorithm for rigid bodies and incompressible flow. Part I: Model problem analysis

DOE PAGES

Banks, J. W.; Henshaw, W. D.; Schwendeman, D. W.; ...

2017-01-20

A stable partitioned algorithm is developed for fluid-structure interaction (FSI) problems involving viscous incompressible flow and rigid bodies. This added-mass partitioned (AMP) algorithm remains stable, without sub-iterations, for light and even zero mass rigid bodies when added-mass and viscous added-damping effects are large. The scheme is based on a generalized Robin interface condition for the fluid pressure that includes terms involving the linear acceleration and angular acceleration of the rigid body. Added mass effects are handled in the Robin condition by inclusion of a boundary integral term that depends on the pressure. Added-damping effects due to the viscous shear forcesmore » on the body are treated by inclusion of added-damping tensors that are derived through a linearization of the integrals defining the force and torque. Added-damping effects may be important at low Reynolds number, or, for example, in the case of a rotating cylinder or rotating sphere when the rotational moments of inertia are small. In this second part of a two-part series, the general formulation of the AMP scheme is presented including the form of the AMP interface conditions and added-damping tensors for general geometries. A fully second-order accurate implementation of the AMP scheme is developed in two dimensions based on a fractional-step method for the incompressible Navier-Stokes equations using finite difference methods and overlapping grids to handle the moving geometry. Here, the numerical scheme is verified on a number of difficult benchmark problems.« less

A Parallel Pipelined Renderer for the Time-Varying Volume Data

NASA Technical Reports Server (NTRS)

Chiueh, Tzi-Cker; Ma, Kwan-Liu

1997-01-01

This paper presents a strategy for efficiently rendering time-varying volume data sets on a distributed-memory parallel computer. Time-varying volume data take large storage space and visualizing them requires reading large files continuously or periodically throughout the course of the visualization process. Instead of using all the processors to collectively render one volume at a time, a pipelined rendering process is formed by partitioning processors into groups to render multiple volumes concurrently. In this way, the overall rendering time may be greatly reduced because the pipelined rendering tasks are overlapped with the I/O required to load each volume into a group of processors; moreover, parallelization overhead may be reduced as a result of partitioning the processors. We modify an existing parallel volume renderer to exploit various levels of rendering parallelism and to study how the partitioning of processors may lead to optimal rendering performance. Two factors which are important to the overall execution time are re-source utilization efficiency and pipeline startup latency. The optimal partitioning configuration is the one that balances these two factors. Tests on Intel Paragon computers show that in general optimal partitionings do exist for a given rendering task and result in 40-50% saving in overall rendering time.

Extended Decentralized Linear-Quadratic-Gaussian Control

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell

2000-01-01

A straightforward extension of a solution to the decentralized linear-Quadratic-Gaussian problem is proposed that allows its use for commonly encountered classes of problems that are currently solved with the extended Kalman filter. This extension allows the system to be partitioned in such a way as to exclude the nonlinearities from the essential algebraic relationships that allow the estimation and control to be optimally decentralized.

Classical statistical mechanics approach to multipartite entanglement

NASA Astrophysics Data System (ADS)

Facchi, P.; Florio, G.; Marzolino, U.; Parisi, G.; Pascazio, S.

2010-06-01

We characterize the multipartite entanglement of a system of n qubits in terms of the distribution function of the bipartite purity over balanced bipartitions. We search for maximally multipartite entangled states, whose average purity is minimal, and recast this optimization problem into a problem of statistical mechanics, by introducing a cost function, a fictitious temperature and a partition function. By investigating the high-temperature expansion, we obtain the first three moments of the distribution. We find that the problem exhibits frustration.

47 CFR 101.1415 - Partitioning and disaggregation.

Code of Federal Regulations, 2010 CFR

2010-10-01

... American Datum (NAD83). (d) Unjust enrichment. 12 GHz licensees that received a bidding credit and... be subject to the provisions concerning unjust enrichment as set forth in § 1.2111 of this chapter...

Clustering, Seriation, and Subset Extraction of Confusion Data

ERIC Educational Resources Information Center

Brusco, Michael J.; Steinley, Douglas

2006-01-01

The study of confusion data is a well established practice in psychology. Although many types of analytical approaches for confusion data are available, among the most common methods are the extraction of 1 or more subsets of stimuli, the partitioning of the complete stimulus set into distinct groups, and the ordering of the stimulus set. Although…

Foreign Language Analysis and Recognition (FLARe)

DTIC Science & Technology

2016-10-08

10 7 Chinese CER ...Rates ( CERs ) were obtained with each feature set: (1) 19.2%, (2) 17.3%, and (3) 15.3%. Based on these results, a GMM-HMM speech recognition system...These systems were evaluated on the HUB4 and HKUST test partitions. Table 7 shows the CER obtained on each test set. Whereas including the HKUST data

Screening-level models to estimate partition ratios of organic chemicals between polymeric materials, air and water.

PubMed

Reppas-Chrysovitsinos, Efstathios; Sobek, Anna; MacLeod, Matthew

2016-06-15

Polymeric materials flowing through the technosphere are repositories of organic chemicals throughout their life cycle. Equilibrium partition ratios of organic chemicals between these materials and air (KMA) or water (KMW) are required for models of fate and transport, high-throughput exposure assessment and passive sampling. KMA and KMW have been measured for a growing number of chemical/material combinations, but significant data gaps still exist. We assembled a database of 363 KMA and 910 KMW measurements for 446 individual compounds and nearly 40 individual polymers and biopolymers, collected from 29 studies. We used the EPI Suite and ABSOLV software packages to estimate physicochemical properties of the compounds and we employed an empirical correlation based on Trouton's rule to adjust the measured KMA and KMW values to a standard reference temperature of 298 K. Then, we used a thermodynamic triangle with Henry's law constant to calculate a complete set of 1273 KMA and KMW values. Using simple linear regression, we developed a suite of single parameter linear free energy relationship (spLFER) models to estimate KMA from the EPI Suite-estimated octanol-air partition ratio (KOA) and KMW from the EPI Suite-estimated octanol-water (KOW) partition ratio. Similarly, using multiple linear regression, we developed a set of polyparameter linear free energy relationship (ppLFER) models to estimate KMA and KMW from ABSOLV-estimated Abraham solvation parameters. We explored the two LFER approaches to investigate (1) their performance in estimating partition ratios, and (2) uncertainties associated with treating all different polymers as a single "bulk" polymeric material compartment. The models we have developed are suitable for screening assessments of the tendency for organic chemicals to be emitted from materials, and for use in multimedia models of the fate of organic chemicals in the indoor environment. In screening applications we recommend that KMA and KMW be modeled as 0.06 ×KOA and 0.06 ×KOW respectively, with an uncertainty range of a factor of 15.

Climatic and physiographic controls of spatial variability in surface water balance over the contiguous United States using the Budyko relationship

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Ficklin, Darren L.

2017-09-01

The geographic variability in the partitioning of precipitation into surface runoff (Q) and evapotranspiration (ET) is fundamental to understanding regional water availability. The Budyko equation suggests this partitioning is strictly a function of aridity, yet observed deviations from this relationship for individual watersheds impede using the framework to model surface water balance in ungauged catchments and under future climate and land use scenarios. A set of climatic, physiographic, and vegetation metrics were used to model the spatial variability in the partitioning of precipitation for 211 watersheds across the contiguous United States (CONUS) within Budyko's framework through the free parameter ω. A generalized additive model found that four widely available variables, precipitation seasonality, the ratio of soil water holding capacity to precipitation, topographic slope, and the fraction of precipitation falling as snow, explained 81.2% of the variability in ω. The ω model applied to the Budyko equation explained 97% of the spatial variability in long-term Q for an independent set of watersheds. The ω model was also applied to estimate the long-term water balance across the CONUS for both contemporary and mid-21st century conditions. The modeled partitioning of observed precipitation to Q and ET compared favorably across the CONUS with estimates from more sophisticated land-surface modeling efforts. For mid-21st century conditions, the model simulated an increase in the fraction of precipitation used by ET across the CONUS with declines in Q for much of the eastern CONUS and mountainous watersheds across the western United States.

Sensitivity of Aerosol Mass and Microphysics to varying treatments of Condensational Growth of Secondary Organic Compounds in a regional model

NASA Astrophysics Data System (ADS)

Lowe, Douglas; Topping, David; McFiggans, Gordon

2017-04-01

Gas to particle partitioning of atmospheric compounds occurs through disequilibrium mass transfer rather than through instantaneous equilibrium. However, it is common to treat only the inorganic compounds as partitioning dynamically whilst organic compounds, represented by the Volatility Basis Set (VBS), are partitioned instantaneously. In this study we implement a more realistic dynamic partitioning of organic compounds in a regional framework and assess impact on aerosol mass and microphysics. It is also common to assume condensed phase water is only associated with inorganic components. We thus also assess sensitivity to assuming all organics are hygroscopic according to their prescribed molecular weight. For this study we use WRF-Chem v3.4.1, focusing on anthropogenic dominated North-Western Europe. Gas-phase chemistry is represented using CBM-Z whilst aerosol dynamics are simulated using the 8-section MOSAIC scheme, including a 9-bin VBS treatment of organic aerosol. Results indicate that predicted mass loadings can vary significantly. Without gas phase ageing of higher volatility compounds, dynamic partitioning always results in lower mass loadings downwind of emission sources. The inclusion of condensed phase water in both partitioning models increases the predicted PM mass, resulting from a larger contribution from higher volatility organics, if present. If gas phase ageing of VBS compounds is allowed to occur in a dynamic model, this can often lead to higher predicted mass loadings, contrary to expected behaviour from a simple non-reactive gas phase box model. As descriptions of aerosol phase processes improve within regional models, the baseline descriptions of partitioning should retain the ability to treat dynamic partitioning of organics compounds. Using our simulations, we discuss whether derived sensitivities to aerosol processes in existing models may be inherently biased. This work was supported by the Natural Environment Research Council within the RONOCO (NE/F004656/1) and CCN-Vol (NE/L007827/1) projects.

Unstructured P2P Network Load Balance Strategy Based on Multilevel Partitioning of Hypergraph

NASA Astrophysics Data System (ADS)

Feng, Lv; Chunlin, Gao; Kaiyang, Ma

2017-05-01

With rapid development of computer performance and distributed technology, P2P-based resource sharing mode plays important role in Internet. P2P network users continued to increase so the high dynamic characteristics of the system determine that it is difficult to obtain the load of other nodes. Therefore, a dynamic load balance strategy based on hypergraph is proposed in this article. The scheme develops from the idea of hypergraph theory in multilevel partitioning. It adopts optimized multilevel partitioning algorithms to partition P2P network into several small areas, and assigns each area a supernode for the management and load transferring of the nodes in this area. In the case of global scheduling is difficult to be achieved, the priority of a number of small range of load balancing can be ensured first. By the node load balance in each small area the whole network can achieve relative load balance. The experiments indicate that the load distribution of network nodes in our scheme is obviously compacter. It effectively solves the unbalanced problems in P2P network, which also improve the scalability and bandwidth utilization of system.

Partitioning in aqueous two-phase systems: Analysis of strengths, weaknesses, opportunities and threats.

PubMed

Soares, Ruben R G; Azevedo, Ana M; Van Alstine, James M; Aires-Barros, M Raquel

2015-08-01

For half a century aqueous two-phase systems (ATPSs) have been applied for the extraction and purification of biomolecules. In spite of their simplicity, selectivity, and relatively low cost they have not been significantly employed for industrial scale bioprocessing. Recently their ability to be readily scaled and interface easily in single-use, flexible biomanufacturing has led to industrial re-evaluation of ATPSs. The purpose of this review is to perform a SWOT analysis that includes a discussion of: (i) strengths of ATPS partitioning as an effective and simple platform for biomolecule purification; (ii) weaknesses of ATPS partitioning in regard to intrinsic problems and possible solutions; (iii) opportunities related to biotechnological challenges that ATPS partitioning may solve; and (iv) threats related to alternative techniques that may compete with ATPS in performance, economic benefits, scale up and reliability. This approach provides insight into the current status of ATPS as a bioprocessing technique and it can be concluded that most of the perceived weakness towards industrial implementation have now been largely overcome, thus paving the way for opportunities in fermentation feed clarification, integration in multi-stage operations and in single-step purification processes. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Field-gradient partitioning for fracture and frictional contact in the material point method: Field-gradient partitioning for fracture and frictional contact in the material point method [Fracture and frictional contact in material point method using damage-field gradients for velocity-field partitioning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Homel, Michael A.; Herbold, Eric B.

Contact and fracture in the material point method require grid-scale enrichment or partitioning of material into distinct velocity fields to allow for displacement or velocity discontinuities at a material interface. We present a new method which a kernel-based damage field is constructed from the particle data. The gradient of this field is used to dynamically repartition the material into contact pairs at each node. Our approach avoids the need to construct and evolve explicit cracks or contact surfaces and is therefore well suited to problems involving complex 3-D fracture with crack branching and coalescence. A straightforward extension of this approachmore » permits frictional ‘self-contact’ between surfaces that are initially part of a single velocity field, enabling more accurate simulation of granular flow, porous compaction, fragmentation, and comminution of brittle materials. Finally, numerical simulations of self contact and dynamic crack propagation are presented to demonstrate the accuracy of the approach.« less

A Dual Super-Element Domain Decomposition Approach for Parallel Nonlinear Finite Element Analysis

NASA Astrophysics Data System (ADS)

Jokhio, G. A.; Izzuddin, B. A.

2015-05-01

This article presents a new domain decomposition method for nonlinear finite element analysis introducing the concept of dual partition super-elements. The method extends ideas from the displacement frame method and is ideally suited for parallel nonlinear static/dynamic analysis of structural systems. In the new method, domain decomposition is realized by replacing one or more subdomains in a "parent system," each with a placeholder super-element, where the subdomains are processed separately as "child partitions," each wrapped by a dual super-element along the partition boundary. The analysis of the overall system, including the satisfaction of equilibrium and compatibility at all partition boundaries, is realized through direct communication between all pairs of placeholder and dual super-elements. The proposed method has particular advantages for matrix solution methods based on the frontal scheme, and can be readily implemented for existing finite element analysis programs to achieve parallelization on distributed memory systems with minimal intervention, thus overcoming memory bottlenecks typically faced in the analysis of large-scale problems. Several examples are presented in this article which demonstrate the computational benefits of the proposed parallel domain decomposition approach and its applicability to the nonlinear structural analysis of realistic structural systems.

Improved image decompression for reduced transform coding artifacts

NASA Technical Reports Server (NTRS)

Orourke, Thomas P.; Stevenson, Robert L.

1994-01-01

The perceived quality of images reconstructed from low bit rate compression is severely degraded by the appearance of transform coding artifacts. This paper proposes a method for producing higher quality reconstructed images based on a stochastic model for the image data. Quantization (scalar or vector) partitions the transform coefficient space and maps all points in a partition cell to a representative reconstruction point, usually taken as the centroid of the cell. The proposed image estimation technique selects the reconstruction point within the quantization partition cell which results in a reconstructed image which best fits a non-Gaussian Markov random field (MRF) image model. This approach results in a convex constrained optimization problem which can be solved iteratively. At each iteration, the gradient projection method is used to update the estimate based on the image model. In the transform domain, the resulting coefficient reconstruction points are projected to the particular quantization partition cells defined by the compressed image. Experimental results will be shown for images compressed using scalar quantization of block DCT and using vector quantization of subband wavelet transform. The proposed image decompression provides a reconstructed image with reduced visibility of transform coding artifacts and superior perceived quality.

Field-gradient partitioning for fracture and frictional contact in the material point method: Field-gradient partitioning for fracture and frictional contact in the material point method [Fracture and frictional contact in material point method using damage-field gradients for velocity-field partitioning

DOE PAGES

Homel, Michael A.; Herbold, Eric B.

2016-08-15

Contact and fracture in the material point method require grid-scale enrichment or partitioning of material into distinct velocity fields to allow for displacement or velocity discontinuities at a material interface. We present a new method which a kernel-based damage field is constructed from the particle data. The gradient of this field is used to dynamically repartition the material into contact pairs at each node. Our approach avoids the need to construct and evolve explicit cracks or contact surfaces and is therefore well suited to problems involving complex 3-D fracture with crack branching and coalescence. A straightforward extension of this approachmore » permits frictional ‘self-contact’ between surfaces that are initially part of a single velocity field, enabling more accurate simulation of granular flow, porous compaction, fragmentation, and comminution of brittle materials. Finally, numerical simulations of self contact and dynamic crack propagation are presented to demonstrate the accuracy of the approach.« less

Integration of domain and resource-based reasoning for real-time control in dynamic environments

NASA Technical Reports Server (NTRS)

Morgan, Keith; Whitebread, Kenneth R.; Kendus, Michael; Cromarty, Andrew S.

1993-01-01

A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

Linear-algebraic bath transformation for simulating complex open quantum systems

DOE PAGES

Huh, Joonsuk; Mostame, Sarah; Fujita, Takatoshi; ...

2014-12-02

In studying open quantum systems, the environment is often approximated as a collection of non-interacting harmonic oscillators, a configuration also known as the star-bath model. It is also well known that the star-bath can be transformed into a nearest-neighbor interacting chain of oscillators. The chain-bath model has been widely used in renormalization group approaches. The transformation can be obtained by recursion relations or orthogonal polynomials. Based on a simple linear algebraic approach, we propose a bath partition strategy to reduce the system-bath coupling strength. As a result, the non-interacting star-bath is transformed into a set of weakly coupled multiple parallelmore » chains. Furthermore, the transformed bath model allows complex problems to be practically implemented on quantum simulators, and it can also be employed in various numerical simulations of open quantum dynamics.« less

Rule groupings in expert systems using nearest neighbour decision rules, and convex hulls

NASA Technical Reports Server (NTRS)

Anastasiadis, Stergios

1991-01-01

Expert System shells are lacking in many areas of software engineering. Large rule based systems are not semantically comprehensible, difficult to debug, and impossible to modify or validate. Partitioning a set of rules found in CLIPS (C Language Integrated Production System) into groups of rules which reflect the underlying semantic subdomains of the problem, will address adequately the concerns stated above. Techniques are introduced to structure a CLIPS rule base into groups of rules that inherently have common semantic information. The concepts involved are imported from the field of A.I., Pattern Recognition, and Statistical Inference. Techniques focus on the areas of feature selection, classification, and a criteria of how 'good' the classification technique is, based on Bayesian Decision Theory. A variety of distance metrics are discussed for measuring the 'closeness' of CLIPS rules and various Nearest Neighbor classification algorithms are described based on the above metric.

A Coupled Approach for Structural Damage Detection with Incomplete Measurements

NASA Technical Reports Server (NTRS)

James, George; Cao, Timothy; Kaouk, Mo; Zimmerman, David

2013-01-01

This historical work couples model order reduction, damage detection, dynamic residual/mode shape expansion, and damage extent estimation to overcome the incomplete measurements problem by using an appropriate undamaged structural model. A contribution of this work is the development of a process to estimate the full dynamic residuals using the columns of a spring connectivity matrix obtained by disassembling the structural stiffness matrix. Another contribution is the extension of an eigenvector filtering procedure to produce full-order mode shapes that more closely match the measured active partition of the mode shapes using a set of modified Ritz vectors. The full dynamic residuals and full mode shapes are used as inputs to the minimum rank perturbation theory to provide an estimate of damage location and extent. The issues associated with this process are also discussed as drivers of near-term development activities to understand and improve this approach.

Aggregation models on hypergraphs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Alberici, Diego, E-mail: diego.alberici2@unibo.it; Contucci, Pierluigi, E-mail: pierluigi.contucci@unibo.it; Mingione, Emanuele, E-mail: emanuele.mingione2@unibo.it

2017-01-15

Following a newly introduced approach by Rasetti and Merelli we investigate the possibility to extract topological information about the space where interacting systems are modelled. From the statistical datum of their observable quantities, like the correlation functions, we show how to reconstruct the activities of their constitutive parts which embed the topological information. The procedure is implemented on a class of polymer models on hypergraphs with hard-core interactions. We show that the model fulfils a set of iterative relations for the partition function that generalise those introduced by Heilmann and Lieb for the monomer–dimer case. After translating those relations intomore » structural identities for the correlation functions we use them to test the precision and the robustness of the inverse problem. Finally the possible presence of a further interaction of peer-to-peer type is considered and a criterion to discover it is identified.« less

Aspects of job scheduling

NASA Technical Reports Server (NTRS)

Phillips, K.

1976-01-01

A mathematical model for job scheduling in a specified context is presented. The model uses both linear programming and combinatorial methods. While designed with a view toward optimization of scheduling of facility and plant operations at the Deep Space Communications Complex, the context is sufficiently general to be widely applicable. The general scheduling problem including options for scheduling objectives is discussed and fundamental parameters identified. Mathematical algorithms for partitioning problems germane to scheduling are presented.

LOOP CALCULUS AND BELIEF PROPAGATION FOR Q-ARY ALPHABET: LOOP TOWER

DOE Office of Scientific and Technical Information (OSTI.GOV)

CHERTKOV, MICHAEL; CHERNYAK, VLADIMIR

Loop calculus introduced in [1], [2] constitutes a new theoretical tool that explicitly expresses symbol Maximum-A-Posteriori (MAP) solution of a general statistical inference problem via a solution of the Belief Propagation (BP) equations. This finding brought a new significance to the BP concept, which in the past was thought of as just a loop-free approximation. In this paper they continue a discussion of the Loop Calculus, partitioning the results into three Sections. In Section 1 they introduce a new formulation of the Loop Calculus in terms of a set of transformations (gauges) that keeping the partition function of the problemmore » invariant. The full expression contains two terms referred to as the 'ground state' and 'excited states' contributions. The BP equations are interpreted as a special (BP) gauge fixing condition that emerges as a special orthogonality constraint between the ground state and excited states, which also selects loop contributions as the only surviving ones among the excited states. In Section 2 they demonstrate how the invariant interpretation of the Loop Calculus, introduced in Section 1, allows a natural extension to the case of a general q-ary alphabet, this is achieved via a loop tower sequential construction. The ground level in the tower is exactly equivalent to assigning one color (out of q available) to the 'ground state' and considering all 'excited' states colored in the remaining (q-1) colors, according to the loop calculus rule. Sequentially, the second level in the tower corresponds to selecting a loop from the previous step, colored in (q-1) colors, and repeating the same ground vs excited states splitting procedure into one and (q-2) colors respectively. The construction proceeds till the full (q-1)-levels deep loop tower (and the corresponding contributions to the partition function) are established. In Section 3 they discuss an ultimate relation between the loop calculus and the Bethe-Free energy variational approach of [3].« less

Sensor/Response Coordination In A Tactical Self-Protection System

NASA Astrophysics Data System (ADS)

Steinberg, Alan N.

1988-08-01

This paper describes a model for integrating information acquisition functions into a response planner within a tactical self-defense system. This model may be used in defining requirements in such applications for sensor systems and for associated processing and control functions. The goal of information acquisition in a self-defense system is generally not that of achieving the best possible estimate of the threat environment; but rather to provide resolution of that environment sufficient to support response decisions. We model the information acquisition problem as that of achieving a partition among possible world states such that the final partition maps into the system's repertoire of possible responses.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Effects of partitioning and scheduling sparse matrix factorization on communication and load balance

NASA Technical Reports Server (NTRS)

Venugopal, Sesh; Naik, Vijay K.

1991-01-01

A block based, automatic partitioning and scheduling methodology is presented for sparse matrix factorization on distributed memory systems. Using experimental results, this technique is analyzed for communication and load imbalance overhead. To study the performance effects, these overheads were compared with those obtained from a straightforward 'wrap mapped' column assignment scheme. All experimental results were obtained using test sparse matrices from the Harwell-Boeing data set. The results show that there is a communication and load balance tradeoff. The block based method results in lower communication cost whereas the wrap mapped scheme gives better load balance.

TriageTools: tools for partitioning and prioritizing analysis of high-throughput sequencing data.

PubMed

Fimereli, Danai; Detours, Vincent; Konopka, Tomasz

2013-04-01

High-throughput sequencing is becoming a popular research tool but carries with it considerable costs in terms of computation time, data storage and bandwidth. Meanwhile, some research applications focusing on individual genes or pathways do not necessitate processing of a full sequencing dataset. Thus, it is desirable to partition a large dataset into smaller, manageable, but relevant pieces. We present a toolkit for partitioning raw sequencing data that includes a method for extracting reads that are likely to map onto pre-defined regions of interest. We show the method can be used to extract information about genes of interest from DNA or RNA sequencing samples in a fraction of the time and disk space required to process and store a full dataset. We report speedup factors between 2.6 and 96, depending on settings and samples used. The software is available at http://www.sourceforge.net/projects/triagetools/.

Anonymous quantum nonlocality.

PubMed

Liang, Yeong-Cherng; Curchod, Florian John; Bowles, Joseph; Gisin, Nicolas

2014-09-26

We investigate the phenomenon of anonymous quantum nonlocality, which refers to the existence of multipartite quantum correlations that are not local in the sense of being Bell-inequality-violating but where the nonlocality is--due to its biseparability with respect to all bipartitions--seemingly nowhere to be found. Such correlations can be produced by the nonlocal collaboration involving definite subset(s) of parties but to an outsider, the identity of these nonlocally correlated parties is completely anonymous. For all n≥3, we present an example of an n-partite quantum correlation exhibiting anonymous nonlocality derived from the n-partite Greenberger-Horne-Zeilinger state. An explicit biseparable decomposition of these correlations is provided for any partitioning of the n parties into two groups. Two applications of these anonymous Greenberger-Horne-Zeilinger correlations in the device-independent setting are discussed: multipartite secret sharing between any two groups of parties and bipartite quantum key distribution that is robust against nearly arbitrary leakage of information.

Unwrapping Students' Ideas about Fractions

ERIC Educational Resources Information Center

Lewis, Rebecca M.; Gibbons, Lynsey K.; Kazemi, Elham; Lind, Teresa

2015-01-01

Supporting students to develop an understanding of the meaning of fractions is an important goal of elementary school mathematics. This involves developing partitioning strategies, creating representations, naming fractional quantities, and using symbolic notation. This article describes how teachers can use a formative assessment problem to…

Exact calculation of loop formation probability identifies folding motifs in RNA secondary structures.

PubMed

Sloma, Michael F; Mathews, David H

2016-12-01

RNA secondary structure prediction is widely used to analyze RNA sequences. In an RNA partition function calculation, free energy nearest neighbor parameters are used in a dynamic programming algorithm to estimate statistical properties of the secondary structure ensemble. Previously, partition functions have largely been used to estimate the probability that a given pair of nucleotides form a base pair, the conditional stacking probability, the accessibility to binding of a continuous stretch of nucleotides, or a representative sample of RNA structures. Here it is demonstrated that an RNA partition function can also be used to calculate the exact probability of formation of hairpin loops, internal loops, bulge loops, or multibranch loops at a given position. This calculation can also be used to estimate the probability of formation of specific helices. Benchmarking on a set of RNA sequences with known secondary structures indicated that loops that were calculated to be more probable were more likely to be present in the known structure than less probable loops. Furthermore, highly probable loops are more likely to be in the known structure than the set of loops predicted in the lowest free energy structures. © 2016 Sloma and Mathews; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Vapor pressures of a homologous series of polyethylene glycols as a reference data set for validating vapor pressure measurement techniques.

NASA Astrophysics Data System (ADS)

Krieger, Ulrich; Marcolli, Claudia; Siegrist, Franziska

2015-04-01

The production of secondary organic aerosol (SOA) by gas-to-particle partitioning is generally represented by an equilibrium partitioning model. A key physical parameter which governs gas-particle partitioning is the pure component vapor pressure, which is difficult to measure for low- and semivolatile compounds. For typical atmospheric compounds like e.g. citric acid or tartaric acid, vapor pressures have been reported in the literature which differ by up to six orders of magnitude [Huisman et al., 2013]. Here, we report vapor pressures of a homologous series of polyethylene glycols (triethylene glycol to octaethylene glycol) determined by measuring the evaporation rate of single, levitated aerosol particles in an electrodynamic balance. We propose to use those as a reference data set for validating different vapor pressure measurement techniques. With each addition of a (O-CH2-CH2)-group the vapor pressure is lowered by about one order of magnitude which makes it easy to detect the lower limit of vapor pressures accessible with a particular technique down to a pressure of 10-8 Pa at room temperature. Reference: Huisman, A. J., Krieger, U. K., Zuend, A., Marcolli, C., and Peter, T., Atmos. Chem. Phys., 13, 6647-6662, 2013.

Ab Initio Predictions of K, He and Ar Partitioning Between Silicate Melt and Liquid Iron Under High Pressure

NASA Astrophysics Data System (ADS)

Xiong, Z.; Tsuchiya, T.

2017-12-01

Element partitioning is an important property in recording geochemical processes during the core-mantle differentiation. However, experimental measurements of element partitioning coefficients under extreme temperature and pressure condition are still challenging. Theoretical modeling is also not easy, because it requires estimation of high temperature Gibbs free energy, which is not directly accessible by the standard molecular dynamics method. We recently developed an original technique to simulate Gibbs free energy based on the thermodynamics integration method[1]. We apply it to element partitioning of geochemical intriguing trace elements between molten silicate and liquid iron such as potassium, helium and argon as starting examples. Radiogenic potassium in the core can provide energy for Earth's magnetic field, convection in the mantle and outer core[2]. However, its partitioning behavior between silicate and iron remains unclear under high pressure[3,4]. Our calculations suggest that a clear positive temperature dependence of the partitioning coefficient but an insignificant pressure effect. Unlike sulfur and silicon, oxygen dissolved in the metals considerably enhances potassium solubility. Calculated electronic structures reveal alkali-metallic feature of potassium in liquid iron, favoring oxygen with strong electron affinity. Our results suggest that 40K could serve as a potential radiogenic heat source in the outer core if oxygen is the major light element therein.­­ We now further extend our technique to partitioning behaviors of other elements, helium and argon, to get insides into the `helium paradox' and `missing argon' problems. References [1] T. Taniuchi, and T. Tsuchiya, Phys.Rev.B. In press [2] B.A. Buffett, H.E. Huppert, J.R. Lister, and A.W. Woods, Geophys.Res.Lett. 29 (1996) 7989-8006. [3] V.R. Murthy, W. Westrenen, and Y. Fei, Nature. 426 (2003) 163-165. [4] A. Corgne, S.Keshav, Y. Fei, and W.F. McDonough, Earth.Planet.Sci.Lett. 256 (2007) 567-576

Partition of some key regulating services in terrestrial ecosystems: Meta-analysis and review.

PubMed

Viglizzo, E F; Jobbágy, E G; Ricard, M F; Paruelo, J M

2016-08-15

Our knowledge about the functional foundations of ecosystem service (ES) provision is still limited and more research is needed to elucidate key functional mechanisms. Using a simplified eco-hydrological scheme, in this work we analyzed how land-use decisions modify the partition of some essential regulatory ES by altering basic relationships between biomass stocks and water flows. A comprehensive meta-analysis and review was conducted based on global, regional and local data from peer-reviewed publications. We analyzed five datasets comprising 1348 studies and 3948 records on precipitation (PPT), aboveground biomass (AGB), AGB change, evapotranspiration (ET), water yield (WY), WY change, runoff (R) and infiltration (I). The conceptual framework was focused on ES that are associated with the ecological functions (e.g., intermediate ES) of ET, WY, R and I. ES included soil protection, carbon sequestration, local climate regulation, water-flow regulation and water recharge. To address the problem of data normality, the analysis included both parametric and non-parametric regression analysis. Results demonstrate that PPT is a first-order biophysical factor that controls ES release at the broader scales. At decreasing scales, ES are partitioned as result of PPT interactions with other biophysical and anthropogenic factors. At intermediate scales, land-use change interacts with PPT modifying ES partition as it the case of afforestation in dry regions, where ET and climate regulation may be enhanced at the expense of R and water-flow regulation. At smaller scales, site-specific conditions such as topography interact with PPT and AGB displaying different ES partition formats. The probable implications of future land-use and climate change on some key ES production and partition are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Metal-silicate partitioning and the light element in the core (Invited)

NASA Astrophysics Data System (ADS)

Wood, B. J.; Wade, J.; Tuff, J.

2009-12-01

Most attempts to constrain the concentrations of “light” elements in the Earth’s core rely either on cosmochemical arguments or on arguments based on the densities and equations of state of Fe-alloys containing the element of concern. Despite its utility, the latter approach yields a wide range of permissible compositions and hence weak constraints. The major problem with the cosmochemical approach is that the abundances in the bulk Earth of all the candidate “light” elements- H, C, O, Si and S are highly uncertain because of their volatile behavior during planetary accretion. In contrast, refractory elements appear to be in approximately CI chondritic relative abundances in the Earth. This leads to the potential for using the partitioning of refractory siderophile elements between the mantle and core to constrain the concentrations of light elements in the core. Recent experimental metal-silicate partitioning data, coupled with mantle abundances of refractory siderophile elements (e.g. Wade and Wood, EPSL v.236, 78—95,2005; Kegler et. al. EPSL v.268, 28-40,2008) have shown that the core segregated from the mantle under high pressure conditions (~40 GPa). If a wide range of elements, from very siderophile, (e.g. Mo) through moderately (Ni, Co, W) to weakly siderophile (V, Cr, Nb, Si) are considered, the Earth also appears to have become more oxidized during accretion. Metal-silicate partitioning of some elements is also sensitive to the light element content of the metal. For example, Nb and W partitioning depend strongly on carbon, Mo on silicon and Cr on sulfur. Given the measured mantle abundances of the refractory elements, these observations enable the Si and C contents of the core to be constrained at ~5% and <2% respectively while partitioning is consistent with a cosmochemically-estimated S content of ~2%.

Partitioning of Organic Ions to Muscle Protein: Experimental Data, Modeling, and Implications for in Vivo Distribution of Organic Ions.

PubMed

Henneberger, Luise; Goss, Kai-Uwe; Endo, Satoshi

2016-07-05

The in vivo partitioning behavior of ionogenic organic chemicals (IOCs) is of paramount importance for their toxicokinetics and bioaccumulation. Among other proteins, structural proteins including muscle proteins could be an important sorption phase for IOCs, because of their high quantity in the human and other animals' body and their polar nature. Binding data for IOCs to structural proteins are, however, severely limited. Therefore, in this study muscle protein-water partition coefficients (KMP/w) of 51 systematically selected organic anions and cations were determined experimentally. A comparison of the measured KMP/w with bovine serum albumin (BSA)-water partition coefficients showed that anionic chemicals sorb more strongly to BSA than to muscle protein (by up to 3.5 orders of magnitude), while cations sorb similarly to both proteins. Sorption isotherms of selected IOCs to muscle protein are linear (i.e., KMP/w is concentration independent), and KMP/w is only marginally influenced by pH value and salt concentration. Using the obtained data set of KMP/w a polyparameter linear free energy relationship (PP-LFER) model was established. The derived equation fits the data well (R(2) = 0.89, RMSE = 0.29). Finally, it was demonstrated that the in vitro measured KMP/w values of this study have the potential to be used to evaluate tissue-plasma partitioning of IOCs in vivo.

Orthogonal recursive bisection data decomposition for high performance computing in cardiac model simulations: dependence on anatomical geometry.

PubMed

Reumann, Matthias; Fitch, Blake G; Rayshubskiy, Aleksandr; Keller, David U J; Seemann, Gunnar; Dossel, Olaf; Pitman, Michael C; Rice, John J

2009-01-01

Orthogonal recursive bisection (ORB) algorithm can be used as data decomposition strategy to distribute a large data set of a cardiac model to a distributed memory supercomputer. It has been shown previously that good scaling results can be achieved using the ORB algorithm for data decomposition. However, the ORB algorithm depends on the distribution of computational load of each element in the data set. In this work we investigated the dependence of data decomposition and load balancing on different rotations of the anatomical data set to achieve optimization in load balancing. The anatomical data set was given by both ventricles of the Visible Female data set in a 0.2 mm resolution. Fiber orientation was included. The data set was rotated by 90 degrees around x, y and z axis, respectively. By either translating or by simply taking the magnitude of the resulting negative coordinates we were able to create 14 data set of the same anatomy with different orientation and position in the overall volume. Computation load ratios for non - tissue vs. tissue elements used in the data decomposition were 1:1, 1:2, 1:5, 1:10, 1:25, 1:38.85, 1:50 and 1:100 to investigate the effect of different load ratios on the data decomposition. The ten Tusscher et al. (2004) electrophysiological cell model was used in monodomain simulations of 1 ms simulation time to compare performance using the different data sets and orientations. The simulations were carried out for load ratio 1:10, 1:25 and 1:38.85 on a 512 processor partition of the IBM Blue Gene/L supercomputer. Th results show that the data decomposition does depend on the orientation and position of the anatomy in the global volume. The difference in total run time between the data sets is 10 s for a simulation time of 1 ms. This yields a difference of about 28 h for a simulation of 10 s simulation time. However, given larger processor partitions, the difference in run time decreases and becomes less significant. Depending on the processor partition size, future work will have to consider the orientation of the anatomy in the global volume for longer simulation runs.

Partition method and experimental validation for impact dynamics of flexible multibody system

NASA Astrophysics Data System (ADS)

Wang, J. Y.; Liu, Z. Y.; Hong, J. Z.

2018-06-01

The impact problem of a flexible multibody system is a non-smooth, high-transient, and strong-nonlinear dynamic process with variable boundary. How to model the contact/impact process accurately and efficiently is one of the main difficulties in many engineering applications. The numerical approaches being used widely in impact analysis are mainly from two fields: multibody system dynamics (MBS) and computational solid mechanics (CSM). Approaches based on MBS provide a more efficient yet less accurate analysis of the contact/impact problems, while approaches based on CSM are well suited for particularly high accuracy needs, yet require very high computational effort. To bridge the gap between accuracy and efficiency in the dynamic simulation of a flexible multibody system with contacts/impacts, a partition method is presented considering that the contact body is divided into two parts, an impact region and a non-impact region. The impact region is modeled using the finite element method to guarantee the local accuracy, while the non-impact region is modeled using the modal reduction approach to raise the global efficiency. A three-dimensional rod-plate impact experiment is designed and performed to validate the numerical results. The principle for how to partition the contact bodies is proposed: the maximum radius of the impact region can be estimated by an analytical method, and the modal truncation orders of the non-impact region can be estimated by the highest frequency of the signal measured. The simulation results using the presented method are in good agreement with the experimental results. It shows that this method is an effective formulation considering both accuracy and efficiency. Moreover, a more complicated multibody impact problem of a crank slider mechanism is investigated to strengthen this conclusion.

a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

NASA Astrophysics Data System (ADS)

Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

2018-04-01

This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

Method of up-front load balancing for local memory parallel processors

NASA Technical Reports Server (NTRS)

Baffes, Paul Thomas (Inventor)

1990-01-01

In a parallel processing computer system with multiple processing units and shared memory, a method is disclosed for uniformly balancing the aggregate computational load in, and utilizing minimal memory by, a network having identical computations to be executed at each connection therein. Read-only and read-write memory are subdivided into a plurality of process sets, which function like artificial processing units. Said plurality of process sets is iteratively merged and reduced to the number of processing units without exceeding the balance load. Said merger is based upon the value of a partition threshold, which is a measure of the memory utilization. The turnaround time and memory savings of the instant method are functions of the number of processing units available and the number of partitions into which the memory is subdivided. Typical results of the preferred embodiment yielded memory savings of from sixty to seventy five percent.

Ergodic theory and visualization. II. Fourier mesochronic plots visualize (quasi)periodic sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levnajić, Zoran; Department of Mechanical Engineering, University of California Santa Barbara, Santa Barbara, California 93106; Mezić, Igor

We present an application and analysis of a visualization method for measure-preserving dynamical systems introduced by I. Mezić and A. Banaszuk [Physica D 197, 101 (2004)], based on frequency analysis and Koopman operator theory. This extends our earlier work on visualization of ergodic partition [Z. Levnajić and I. Mezić, Chaos 20, 033114 (2010)]. Our method employs the concept of Fourier time average [I. Mezić and A. Banaszuk, Physica D 197, 101 (2004)], and is realized as a computational algorithms for visualization of periodic and quasi-periodic sets in the phase space. The complement of periodic phase space partition contains chaotic zone,more » and we show how to identify it. The range of method's applicability is illustrated using well-known Chirikov standard map, while its potential in illuminating higher-dimensional dynamics is presented by studying the Froeschlé map and the Extended Standard Map.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rivasseau, Vincent, E-mail: vincent.rivasseau@th.u-psud.fr, E-mail: adrian.tanasa@ens-lyon.org; Tanasa, Adrian, E-mail: vincent.rivasseau@th.u-psud.fr, E-mail: adrian.tanasa@ens-lyon.org

The Loop Vertex Expansion (LVE) is a quantum field theory (QFT) method which explicitly computes the Borel sum of Feynman perturbation series. This LVE relies in a crucial way on symmetric tree weights which define a measure on the set of spanning trees of any connected graph. In this paper we generalize this method by defining new tree weights. They depend on the choice of a partition of a set of vertices of the graph, and when the partition is non-trivial, they are no longer symmetric under permutation of vertices. Nevertheless we prove they have the required positivity property tomore » lead to a convergent LVE; in fact we formulate this positivity property precisely for the first time. Our generalized tree weights are inspired by the Brydges-Battle-Federbush work on cluster expansions and could be particularly suited to the computation of connected functions in QFT. Several concrete examples are explicitly given.« less

Ergodic theory and visualization. II. Fourier mesochronic plots visualize (quasi)periodic sets.

PubMed

Levnajić, Zoran; Mezić, Igor

2015-05-01

We present an application and analysis of a visualization method for measure-preserving dynamical systems introduced by I. Mezić and A. Banaszuk [Physica D 197, 101 (2004)], based on frequency analysis and Koopman operator theory. This extends our earlier work on visualization of ergodic partition [Z. Levnajić and I. Mezić, Chaos 20, 033114 (2010)]. Our method employs the concept of Fourier time average [I. Mezić and A. Banaszuk, Physica D 197, 101 (2004)], and is realized as a computational algorithms for visualization of periodic and quasi-periodic sets in the phase space. The complement of periodic phase space partition contains chaotic zone, and we show how to identify it. The range of method's applicability is illustrated using well-known Chirikov standard map, while its potential in illuminating higher-dimensional dynamics is presented by studying the Froeschlé map and the Extended Standard Map.

Bayesian approach to inverse statistical mechanics.

PubMed

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Bayesian approach to inverse statistical mechanics

NASA Astrophysics Data System (ADS)

Habeck, Michael

2014-05-01

Inverse statistical mechanics aims to determine particle interactions from ensemble properties. This article looks at this inverse problem from a Bayesian perspective and discusses several statistical estimators to solve it. In addition, a sequential Monte Carlo algorithm is proposed that draws the interaction parameters from their posterior probability distribution. The posterior probability involves an intractable partition function that is estimated along with the interactions. The method is illustrated for inverse problems of varying complexity, including the estimation of a temperature, the inverse Ising problem, maximum entropy fitting, and the reconstruction of molecular interaction potentials.

Determining metal origins and availability in fluvial deposits by analysis of geochemical baselines and solid-solution partitioning measurements and modelling.

PubMed

Vijver, Martina G; Spijker, Job; Vink, Jos P M; Posthuma, Leo

2008-12-01

Metals in floodplain soils and sediments (deposits) can originate from lithogenic and anthropogenic sources, and their availability for uptake in biota is hypothesized to depend on both origin and local sediment conditions. In criteria-based environmental risk assessments, these issues are often neglected, implying local risks to be often over-estimated. Current problem definitions in river basin management tend to require a refined, site-specific focus, resulting in a need to address both aspects. This paper focuses on the determination of local environmental availabilities of metals in fluvial deposits by addressing both the origins of the metals and their partitioning over the solid and solution phases. The environmental availability of metals is assumed to be a key force influencing exposure levels in field soils and sediments. Anthropogenic enrichments of Cu, Zn and Pb in top layers could be distinguished from lithogenic background concentrations and described using an aluminium-proxy. Cd in top layers was attributed to anthropogenic enrichment almost fully. Anthropogenic enrichments for Cu and Zn appeared further to be also represented by cold 2M HNO3 extraction of site samples. For Pb the extractions over-estimated the enrichments. Metal partitioning was measured, and measurements were compared to predictions generated by an empirical regression model and by a mechanistic-kinetic model. The partitioning models predicted metal partitioning in floodplain deposits within about one order of magnitude, though a large inter-sample variability was found for Pb.

Segmentation schema for enhancing land cover identification: A case study using Sentinel 2 data

NASA Astrophysics Data System (ADS)

Mongus, Domen; Žalik, Borut

2018-04-01

Land monitoring is performed increasingly using high and medium resolution optical satellites, such as the Sentinel-2. However, optical data is inevitably subjected to the variable operational conditions under which it was acquired. Overlapping of features caused by shadows, soft transitions between shadowed and non-shadowed regions, and temporal variability of the observed land-cover types require radiometric corrections. This study examines a new approach to enhancing the accuracy of land cover identification that resolves this problem. The proposed method constructs an ensemble-type classification model with weak classifiers tuned to the particular operational conditions under which the data was acquired. Iterative segmentation over the learning set is applied for this purpose, where feature space is partitioned according to the likelihood of misclassifications introduced by the classification model. As these are a consequence of overlapping features, such partitioning avoids the need for radiometric corrections of the data, and divides land cover types implicitly into subclasses. As a result, improved performance of all tested classification approaches were measured during the validation that was conducted on Sentinel-2 data. The highest accuracies in terms of F1-scores were achieved using the Naive Bayes Classifier as the weak classifier, while supplementing original spectral signatures with normalised difference vegetation index and texture analysis features, namely, average intensity, contrast, homogeneity, and dissimilarity. In total, an F1-score of nearly 95% was achieved in this way, with F1-scores of each particular land cover type reaching above 90%.

An approximate block Newton method for coupled iterations of nonlinear solvers: Theory and conjugate heat transfer applications

NASA Astrophysics Data System (ADS)

Yeckel, Andrew; Lun, Lisa; Derby, Jeffrey J.

2009-12-01

A new, approximate block Newton (ABN) method is derived and tested for the coupled solution of nonlinear models, each of which is treated as a modular, black box. Such an approach is motivated by a desire to maintain software flexibility without sacrificing solution efficiency or robustness. Though block Newton methods of similar type have been proposed and studied, we present a unique derivation and use it to sort out some of the more confusing points in the literature. In particular, we show that our ABN method behaves like a Newton iteration preconditioned by an inexact Newton solver derived from subproblem Jacobians. The method is demonstrated on several conjugate heat transfer problems modeled after melt crystal growth processes. These problems are represented by partitioned spatial regions, each modeled by independent heat transfer codes and linked by temperature and flux matching conditions at the boundaries common to the partitions. Whereas a typical block Gauss-Seidel iteration fails about half the time for the model problem, quadratic convergence is achieved by the ABN method under all conditions studied here. Additional performance advantages over existing methods are demonstrated and discussed.

Strong coupling strategy for fluid-structure interaction problems in supersonic regime via fixed point iteration

NASA Astrophysics Data System (ADS)

Storti, Mario A.; Nigro, Norberto M.; Paz, Rodrigo R.; Dalcín, Lisandro D.

2009-03-01

In this paper some results on the convergence of the Gauss-Seidel iteration when solving fluid/structure interaction problems with strong coupling via fixed point iteration are presented. The flow-induced vibration of a flat plate aligned with the flow direction at supersonic Mach number is studied. The precision of different predictor schemes and the influence of the partitioned strong coupling on stability is discussed.

Can Kindergartners Do Fractions?

ERIC Educational Resources Information Center

Cwikla, Julie

2014-01-01

Mathematics professor Julie Cwikla decided that she needed to investigate young children's understandings and see what precurricular partitioning notions young minds bring to the fraction table. Cwikla realized that only a handful of studies have examined how preschool-age and early elementary school-age students solve fraction problems (Empson…

WHEN ISOTOPES AREN'T ENOUGH: ADDITIONAL INFORMATION TO CONSTRAIN MIXING PROBLEMS

EPA Science Inventory

Stable isotopes are often used as chemical tracers to determine the relative contributions of sources to a mixture. Ecological examples include partitioning pollution sources to air or water bodies, trophic links in food webs, plant water use from different soil horizons, source...

MATERIALS FOR MODERNIZATION.

ERIC Educational Resources Information Center

JACKSON, R. GRAHAM

CHOICES AND ISSUES IN SELECTING MATERIALS FOR MODERNIZATION OF SCHOOL BUILDINGS ARE DISCUSSED IN THIS REPORT. BACKGROUND INFORMATION IS INTRODUCED IN TERMS OF REASONS FOR ABANDONMENT, THE CAUSES AND EFFECTS OF SCHOOL BUILDING OBSOLESCENCE, AND PROBLEMS IN THE MODERNIZATION PROCESS. INTERIOR PARTITIONS ARE DISCUSSED IN TERMS OF BUILDING MATERIALS,…

Protein and gene model inference based on statistical modeling in k-partite graphs.

PubMed

Gerster, Sarah; Qeli, Ermir; Ahrens, Christian H; Bühlmann, Peter

2010-07-06

One of the major goals of proteomics is the comprehensive and accurate description of a proteome. Shotgun proteomics, the method of choice for the analysis of complex protein mixtures, requires that experimentally observed peptides are mapped back to the proteins they were derived from. This process is also known as protein inference. We present Markovian Inference of Proteins and Gene Models (MIPGEM), a statistical model based on clearly stated assumptions to address the problem of protein and gene model inference for shotgun proteomics data. In particular, we are dealing with dependencies among peptides and proteins using a Markovian assumption on k-partite graphs. We are also addressing the problems of shared peptides and ambiguous proteins by scoring the encoding gene models. Empirical results on two control datasets with synthetic mixtures of proteins and on complex protein samples of Saccharomyces cerevisiae, Drosophila melanogaster, and Arabidopsis thaliana suggest that the results with MIPGEM are competitive with existing tools for protein inference.

Automated problem scheduling and reduction of synchronization delay effects

NASA Technical Reports Server (NTRS)

Saltz, Joel H.

1987-01-01

It is anticipated that in order to make effective use of many future high performance architectures, programs will have to exhibit at least a medium grained parallelism. A framework is presented for partitioning very sparse triangular systems of linear equations that is designed to produce favorable preformance results in a wide variety of parallel architectures. Efficient methods for solving these systems are of interest because: (1) they provide a useful model problem for use in exploring heuristics for the aggregation, mapping and scheduling of relatively fine grained computations whose data dependencies are specified by directed acrylic graphs, and (2) because such efficient methods can find direct application in the development of parallel algorithms for scientific computation. Simple expressions are derived that describe how to schedule computational work with varying degrees of granularity. The Encore Multimax was used as a hardware simulator to investigate the performance effects of using the partitioning techniques presented in shared memory architectures with varying relative synchronization costs.

Partitioning technique for open systems

NASA Astrophysics Data System (ADS)

Brändas, Erkki J.

2010-11-01

The focus of the present contribution is essentially confined to three research areas carried out during the author's turns as visiting (assistant, associate and full) professor at the University of Florida's Quantum Theory Project, QTP. The first two topics relate to perturbation theory and spectral theory for self-adjoint operators in Hilbert space. The third subject concerns analytic extensions to non-self-adjoint problems, where particular consequences of the occurrence of continuous energy spectra are measured. In these studies general partitioning methods serve as general cover for perturbation-, variational- and general matrix theory. In addition we follow up associated inferences for the time dependent problem as well as recent results and conclusions of a rather general yet surprising character. Although the author spent most of his times at QTP during visits in the 1970s and 1980s, collaborations with department members and shorter stays continued through later decades. Nevertheless the impact must be somewhat fragmentary, yet it is hoped that the present account is sufficiently self-contained to be realistic and constructive.

Compile-time estimation of communication costs in multicomputers

NASA Technical Reports Server (NTRS)

Gupta, Manish; Banerjee, Prithviraj

1991-01-01

An important problem facing numerous research projects on parallelizing compilers for distributed memory machines is that of automatically determining a suitable data partitioning scheme for a program. Any strategy for automatic data partitioning needs a mechanism for estimating the performance of a program under a given partitioning scheme, the most crucial part of which involves determining the communication costs incurred by the program. A methodology is described for estimating the communication costs at compile-time as functions of the numbers of processors over which various arrays are distributed. A strategy is described along with its theoretical basis, for making program transformations that expose opportunities for combining of messages, leading to considerable savings in the communication costs. For certain loops with regular dependences, the compiler can detect the possibility of pipelining, and thus estimate communication costs more accurately than it could otherwise. These results are of great significance to any parallelization system supporting numeric applications on multicomputers. In particular, they lay down a framework for effective synthesis of communication on multicomputers from sequential program references.

Scalable detection of statistically significant communities and hierarchies, using message passing for modularity

PubMed Central

Zhang, Pan; Moore, Cristopher

2014-01-01

Modularity is a popular measure of community structure. However, maximizing the modularity can lead to many competing partitions, with almost the same modularity, that are poorly correlated with each other. It can also produce illusory ‘‘communities’’ in random graphs where none exist. We address this problem by using the modularity as a Hamiltonian at finite temperature and using an efficient belief propagation algorithm to obtain the consensus of many partitions with high modularity, rather than looking for a single partition that maximizes it. We show analytically and numerically that the proposed algorithm works all of the way down to the detectability transition in networks generated by the stochastic block model. It also performs well on real-world networks, revealing large communities in some networks where previous work has claimed no communities exist. Finally we show that by applying our algorithm recursively, subdividing communities until no statistically significant subcommunities can be found, we can detect hierarchical structure in real-world networks more efficiently than previous methods. PMID:25489096

Space and Time Partitioning with Hardware Support for Space Applications

NASA Astrophysics Data System (ADS)

Pinto, S.; Tavares, A.; Montenegro, S.

2016-08-01

Complex and critical systems like airplanes and spacecraft implement a very fast growing amount of functions. Typically, those systems were implemented with fully federated architectures, but the number and complexity of desired functions of todays systems led aerospace industry to follow another strategy. Integrated Modular Avionics (IMA) arose as an attractive approach for consolidation, by combining several applications into one single generic computing resource. Current approach goes towards higher integration provided by space and time partitioning (STP) of system virtualization. The problem is existent virtualization solutions are not ready to fully provide what the future of aerospace are demanding: performance, flexibility, safety, security while simultaneously containing Size, Weight, Power and Cost (SWaP-C).This work describes a real time hypervisor for space applications assisted by commercial off-the-shell (COTS) hardware. ARM TrustZone technology is exploited to implement a secure virtualization solution with low overhead and low memory footprint. This is demonstrated by running multiple guest partitions of RODOS operating system on a Xilinx Zynq platform.

Computing black hole partition functions from quasinormal modes

DOE PAGES

Arnold, Peter; Szepietowski, Phillip; Vaman, Diana

2016-07-07

We propose a method of computing one-loop determinants in black hole space-times (with emphasis on asymptotically anti-de Sitter black holes) that may be used for numerics when completely-analytic results are unattainable. The method utilizes the expression for one-loop determinants in terms of quasinormal frequencies determined by Denef, Hartnoll and Sachdev in [1]. A numerical evaluation must face the fact that the sum over the quasinormal modes, indexed by momentum and overtone numbers, is divergent. A necessary ingredient is then a regularization scheme to handle the divergent contributions of individual fixed-momentum sectors to the partition function. To this end, we formulatemore » an effective two-dimensional problem in which a natural refinement of standard heat kernel techniques can be used to account for contributions to the partition function at fixed momentum. We test our method in a concrete case by reproducing the scalar one-loop determinant in the BTZ black hole background. Furthermore, we then discuss the application of such techniques to more complicated spacetimes.« less

Sensor And Method For Detecting A Superstrate

NASA Technical Reports Server (NTRS)

Arndt, G. Dickey (Inventor); Cari, James R. (Inventor); Ngo, Phong H. (Inventor); Fink, Patrick W. (Inventor); Siekierski, James D. (Inventor)

2006-01-01

Method and apparatus are provided for determining a superstrate on or near a sensor, e.g., for detecting the presence of an ice superstrate on an airplane wing or a road. In one preferred embodiment, multiple measurement cells are disposed along a transmission line. While the present invention is operable with different types of transmission lines, construction details for a presently preferred coplanar waveguide and a microstrip waveguide are disclosed. A computer simulation is provided as part of the invention for predicting results of a simulated superstrate detector system. The measurement cells may be physically partitioned, nonphysically partitioned with software or firmware, or include a combination of different types of partitions. In one embodiment, a plurality of transmission lines are utilized wherein each transmission line includes a plurality of measurement cells. The plurality of transmission lines may be multiplexed with the signal from each transmission line being applied to the same phase detector. In one embodiment, an inverse problem method is applied to determine the superstrate dielectric for a transmission line with multiple measurement cells.

Estimating the octanol/water partition coefficient for aliphatic organic compounds using semi-empirical electrotopological index.

PubMed

Souza, Erica Silva; Zaramello, Laize; Kuhnen, Carlos Alberto; Junkes, Berenice da Silva; Yunes, Rosendo Augusto; Heinzen, Vilma Edite Fonseca

2011-01-01

A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (I(SET)). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the I(SET) in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P.

Optimization of Sample Points for Monitoring Arable Land Quality by Simulated Annealing while Considering Spatial Variations

PubMed Central

Wang, Junxiao; Wang, Xiaorui; Zhou, Shenglu; Wu, Shaohua; Zhu, Yan; Lu, Chunfeng

2016-01-01

With China’s rapid economic development, the reduction in arable land has emerged as one of the most prominent problems in the nation. The long-term dynamic monitoring of arable land quality is important for protecting arable land resources. An efficient practice is to select optimal sample points while obtaining accurate predictions. To this end, the selection of effective points from a dense set of soil sample points is an urgent problem. In this study, data were collected from Donghai County, Jiangsu Province, China. The number and layout of soil sample points are optimized by considering the spatial variations in soil properties and by using an improved simulated annealing (SA) algorithm. The conclusions are as follows: (1) Optimization results in the retention of more sample points in the moderate- and high-variation partitions of the study area; (2) The number of optimal sample points obtained with the improved SA algorithm is markedly reduced, while the accuracy of the predicted soil properties is improved by approximately 5% compared with the raw data; (3) With regard to the monitoring of arable land quality, a dense distribution of sample points is needed to monitor the granularity. PMID:27706051

Egocentric daily activity recognition via multitask clustering.

PubMed

Yan, Yan; Ricci, Elisa; Liu, Gaowen; Sebe, Nicu

2015-10-01

Recognizing human activities from videos is a fundamental research problem in computer vision. Recently, there has been a growing interest in analyzing human behavior from data collected with wearable cameras. First-person cameras continuously record several hours of their wearers' life. To cope with this vast amount of unlabeled and heterogeneous data, novel algorithmic solutions are required. In this paper, we propose a multitask clustering framework for activity of daily living analysis from visual data gathered from wearable cameras. Our intuition is that, even if the data are not annotated, it is possible to exploit the fact that the tasks of recognizing everyday activities of multiple individuals are related, since typically people perform the same actions in similar environments, e.g., people working in an office often read and write documents). In our framework, rather than clustering data from different users separately, we propose to look for clustering partitions which are coherent among related tasks. In particular, two novel multitask clustering algorithms, derived from a common optimization problem, are introduced. Our experimental evaluation, conducted both on synthetic data and on publicly available first-person vision data sets, shows that the proposed approach outperforms several single-task and multitask learning methods.

Reprint of Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

NASA Astrophysics Data System (ADS)

D'Ambra, Pasqua; Tartaglione, Gaetano

2015-04-01

Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method

NASA Astrophysics Data System (ADS)

D'Ambra, Pasqua; Tartaglione, Gaetano

2015-03-01

Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.

Energy Decomposition Analysis Based on Absolutely Localized Molecular Orbitals for Large-Scale Density Functional Theory Calculations in Drug Design.

PubMed

Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2016-07-12

We report the development and implementation of an energy decomposition analysis (EDA) scheme in the ONETEP linear-scaling electronic structure package. Our approach is hybrid as it combines the localized molecular orbital EDA (Su, P.; Li, H. J. Chem. Phys., 2009, 131, 014102) and the absolutely localized molecular orbital EDA (Khaliullin, R. Z.; et al. J. Phys. Chem. A, 2007, 111, 8753-8765) to partition the intermolecular interaction energy into chemically distinct components (electrostatic, exchange, correlation, Pauli repulsion, polarization, and charge transfer). Limitations shared in EDA approaches such as the issue of basis set dependence in polarization and charge transfer are discussed, and a remedy to this problem is proposed that exploits the strictly localized property of the ONETEP orbitals. Our method is validated on a range of complexes with interactions relevant to drug design. We demonstrate the capabilities for large-scale calculations with our approach on complexes of thrombin with an inhibitor comprised of up to 4975 atoms. Given the capability of ONETEP for large-scale calculations, such as on entire proteins, we expect that our EDA scheme can be applied in a large range of biomolecular problems, especially in the context of drug design.

Organic Carbon/Water and Dissolved Organic Carbon/Water Partitioning of Cyclic Volatile Methylsiloxanes: Measurements and Polyparameter Linear Free Energy Relationships.

PubMed

Panagopoulos, Dimitri; Jahnke, Annika; Kierkegaard, Amelie; MacLeod, Matthew

2015-10-20

The sorption of cyclic volatile methyl siloxanes (cVMS) to organic matter has a strong influence on their fate in the aquatic environment. We report new measurements of the partition ratios between freshwater sediment organic carbon and water (KOC) and between Aldrich humic acid dissolved organic carbon and water (KDOC) for three cVMS, and for three polychlorinated biphenyls (PCBs) that were used as reference chemicals. Our measurements were made using a purge-and-trap method that employs benchmark chemicals to calibrate mass transfer at the air/water interface in a fugacity-based multimedia model. The measured log KOC of octamethylcyclotetrasiloxane (D4), decamethylcyclopentasiloxane (D5), and dodecamethylcyclohexasiloxane (D6) were 5.06, 6.12, and 7.07, and log KDOC were 5.05, 6.13, and 6.79. To our knowledge, our measurements for KOC of D6 and KDOC of D4 and D6 are the first reported. Polyparameter linear free energy relationships (PP-LFERs) derived from training sets of empirical data that did not include cVMS generally did not predict our measured partition ratios of cVMS accurately (root-mean-squared-error (RMSE) for logKOC 0.76 and for logKDOC 0.73). We constructed new PP-LFERs that accurately describe partition ratios for the cVMS as well as for other chemicals by including our new measurements in the existing training sets (logKOC RMSEcVMS: 0.09, logKDOC RMSEcVMS: 0.12). The PP-LFERs we have developed here should be further evaluated and perhaps recalibrated when experimental data for other siloxanes become available.

Partitioning and interfacial tracers for differentiating NAPL entrapment configuration: column-scale investigation.

PubMed

Dai, D; Barranco, F T; Illangasekare, T H

2001-12-15

Research on the use of partitioning and interfacial tracers has led to the development of techniques for estimating subsurface NAPL amount and NAPL-water interfacial area. Although these techniques have been utilized with some success at field sites, current application is limited largely to NAPL at residual saturation, such as for the case of post-remediation settings where mobile NAPL has been removed through product recovery. The goal of this study was to fundamentally evaluate partitioning and interfacial tracer behavior in controlled column-scale test cells for a range of entrapment configurations varying in NAPL saturation, with the results serving as a determinant of technique efficacy (and design protocol) for use with complexly distributed NAPLs, possibly at high saturation, in heterogeneous aquifers. Representative end members of the range of entrapment configurations observed under conditions of natural heterogeneity (an occurrence with residual NAPL saturation [discontinuous blobs] and an occurrence with high NAPL saturation [continuous free-phase LNAPL lens]) were evaluated. Study results indicated accurate prediction (using measured tracer retardation and equilibrium-based computational techniques) of NAPL amount and NAPL-water interfacial area for the case of residual NAPL saturation. For the high-saturation LNAPL lens, results indicated that NAPL-water interfacial area, but not NAPL amount (underpredicted by 35%), can be reasonably determined using conventional computation techniques. Underprediction of NAPL amount lead to an erroneous prediction of NAPL distribution, as indicated by the NAPL morphology index. In light of these results, careful consideration should be given to technique design and critical assumptions before applying equilibrium-based partitioning tracer methodology to settings where NAPLs are complexly entrapped, such as in naturally heterogeneous subsurface formations.

Effect of video server topology on contingency capacity requirements

NASA Astrophysics Data System (ADS)

Kienzle, Martin G.; Dan, Asit; Sitaram, Dinkar; Tetzlaff, William H.

1996-03-01

Video servers need to assign a fixed set of resources to each video stream in order to guarantee on-time delivery of the video data. If a server has insufficient resources to guarantee the delivery, it must reject the stream request rather than slowing down all existing streams. Large scale video servers are being built as clusters of smaller components, so as to be economical, scalable, and highly available. This paper uses a blocking model developed for telephone systems to evaluate video server cluster topologies. The goal is to achieve high utilization of the components and low per-stream cost combined with low blocking probability and high user satisfaction. The analysis shows substantial economies of scale achieved by larger server images. Simple distributed server architectures can result in partitioning of resources with low achievable resource utilization. By comparing achievable resource utilization of partitioned and monolithic servers, we quantify the cost of partitioning. Next, we present an architecture for a distributed server system that avoids resource partitioning and results in highly efficient server clusters. Finally, we show how, in these server clusters, further optimizations can be achieved through caching and batching of video streams.

Computational solvent system screening for the separation of tocopherols with centrifugal partition chromatography using deep eutectic solvent-based biphasic systems.

PubMed

Bezold, Franziska; Weinberger, Maria E; Minceva, Mirjana

2017-03-31

Tocopherols are a class of molecules with vitamin E activity. Among those, α-tocopherol is the most important vitamin E source in the human diet. The purification of tocopherols involving biphasic liquid systems can be challenging since these vitamins are poorly soluble in water. Deep eutectic solvents (DES) can be used to form water-free biphasic systems and have already proven applicable for centrifugal partition chromatography separations. In this work, a computational solvent system screening was performed using the predictive thermodynamic model COSMO-RS. Liquid-liquid equilibria of solvent systems composed of alkanes, alcohols and DES, as well as partition coefficients of α-tocopherol, β-tocopherol, γ-tocopherol, and σ-tocopherol in these biphasic solvent systems were calculated. From the results the best suited biphasic solvent system, namely heptane/ethanol/choline chloride-1,4-butanediol, was chosen and a batch injection of a tocopherol mixture, mainly consisting of α- and γ-tocopherol, was performed using a centrifugal partition chromatography set up (SCPE 250-BIO). A separation factor of 1.74 was achieved for α- and γ-tocopherol. Copyright © 2017 Elsevier B.V. All rights reserved.

Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles.

PubMed

Snyder, David A; Montelione, Gaetano T

2005-06-01

An important open question in the field of NMR-based biomolecular structure determination is how best to characterize the precision of the resulting ensemble of structures. Typically, the RMSD, as minimized in superimposing the ensemble of structures, is the preferred measure of precision. However, the presence of poorly determined atomic coordinates and multiple "RMSD-stable domains"--locally well-defined regions that are not aligned in global superimpositions--complicate RMSD calculations. In this paper, we present a method, based on a novel, structurally defined order parameter, for identifying a set of core atoms to use in determining superimpositions for RMSD calculations. In addition we present a method for deciding whether to partition that core atom set into "RMSD-stable domains" and, if so, how to determine partitioning of the core atom set. We demonstrate our algorithm and its application in calculating statistically sound RMSD values by applying it to a set of NMR-derived structural ensembles, superimposing each RMSD-stable domain (or the entire core atom set, where appropriate) found in each protein structure under consideration. A parameter calculated by our algorithm using a novel, kurtosis-based criterion, the epsilon-value, is a measure of precision of the superimposition that complements the RMSD. In addition, we compare our algorithm with previously described algorithms for determining core atom sets. The methods presented in this paper for biomolecular structure superimposition are quite general, and have application in many areas of structural bioinformatics and structural biology.

WHEN ISOTOPES AREN'T ENOUGH: USING ADDITIONAL INFORMATION TO CONSTRAIN MIXING PROBLEMS

EPA Science Inventory

Stable isotopes are often used as chemical tracers to determine the relative contributions of sources to a mixture. Ecological examples include partitioning pollution sources to air or water bodies, trophic links in food webs, plant water use from different soil horizons, source...

Equivalent Colorings with "Maple"

ERIC Educational Resources Information Center

Cecil, David R.; Wang, Rongdong

2005-01-01

Many counting problems can be modeled as "colorings" and solved by considering symmetries and Polya's cycle index polynomial. This paper presents a "Maple 7" program link http://users.tamuk.edu/kfdrc00/ that, given Polya's cycle index polynomial, determines all possible associated colorings and their partitioning into equivalence classes. These…

Load Balancing Unstructured Adaptive Grids for CFD Problems

NASA Technical Reports Server (NTRS)

Biswas, Rupak; Oliker, Leonid

1996-01-01

Mesh adaption is a powerful tool for efficient unstructured-grid computations but causes load imbalance among processors on a parallel machine. A dynamic load balancing method is presented that balances the workload across all processors with a global view. After each parallel tetrahedral mesh adaption, the method first determines if the new mesh is sufficiently unbalanced to warrant a repartitioning. If so, the adapted mesh is repartitioned, with new partitions assigned to processors so that the redistribution cost is minimized. The new partitions are accepted only if the remapping cost is compensated by the improved load balance. Results indicate that this strategy is effective for large-scale scientific computations on distributed-memory multiprocessors.

SEU System Analysis: Not Just the Sum of All Parts

NASA Technical Reports Server (NTRS)

Berg, Melanie D.; Label, Kenneth

2014-01-01

Single event upset (SEU) analysis of complex systems is challenging. Currently, system SEU analysis is performed by component level partitioning and then either: the most dominant SEU cross-sections (SEUs) are used in system error rate calculations; or the partition SEUs are summed to eventually obtain a system error rate. In many cases, system error rates are overestimated because these methods generally overlook system level derating factors. The problem with overestimating is that it can cause overdesign and consequently negatively affect the following: cost, schedule, functionality, and validation/verification. The scope of this presentation is to discuss the risks involved with our current scheme of SEU analysis for complex systems; and to provide alternative methods for improvement.

An Energy-Based Approach for Detection and Characterization of Subtle Entities Within Laser Scanning Point-Clouds

NASA Astrophysics Data System (ADS)

Arav, Reuma; Filin, Sagi

2016-06-01

Airborne laser scans present an optimal tool to describe geomorphological features in natural environments. However, a challenge arises in the detection of such phenomena, as they are embedded in the topography, tend to blend into their surroundings and leave only a subtle signature within the data. Most object-recognition studies address mainly urban environments and follow a general pipeline where the data are partitioned into segments with uniform properties. These approaches are restricted to man-made domain and are capable to handle limited features that answer a well-defined geometric form. As natural environments present a more complex set of features, the common interpretation of the data is still manual at large. In this paper, we propose a data-aware detection scheme, unbound to specific domains or shapes. We define the recognition question as an energy optimization problem, solved by variational means. Our approach, based on the level-set method, characterizes geometrically local surfaces within the data, and uses these characteristics as potential field for minimization. The main advantage here is that it allows topological changes of the evolving curves, such as merging and breaking. We demonstrate the proposed methodology on the detection of collapse sinkholes.

Optimization of Error-Bounded Lossy Compression for Hard-to-Compress HPC Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Di, Sheng; Cappello, Franck

Since today’s scientific applications are producing vast amounts of data, compressing them before storage/transmission is critical. Results of existing compressors show two types of HPC data sets: highly compressible and hard to compress. In this work, we carefully design and optimize the error-bounded lossy compression for hard-tocompress scientific data. We propose an optimized algorithm that can adaptively partition the HPC data into best-fit consecutive segments each having mutually close data values, such that the compression condition can be optimized. Another significant contribution is the optimization of shifting offset such that the XOR-leading-zero length between two consecutive unpredictable data points canmore » be maximized. We finally devise an adaptive method to select the best-fit compressor at runtime for maximizing the compression factor. We evaluate our solution using 13 benchmarks based on real-world scientific problems, and we compare it with 9 other state-of-the-art compressors. Experiments show that our compressor can always guarantee the compression errors within the user-specified error bounds. Most importantly, our optimization can improve the compression factor effectively, by up to 49% for hard-tocompress data sets with similar compression/decompression time cost.« less

The island dynamics model on parallel quadtree grids

NASA Astrophysics Data System (ADS)

Mistani, Pouria; Guittet, Arthur; Bochkov, Daniil; Schneider, Joshua; Margetis, Dionisios; Ratsch, Christian; Gibou, Frederic

2018-05-01

We introduce an approach for simulating epitaxial growth by use of an island dynamics model on a forest of quadtree grids, and in a parallel environment. To this end, we use a parallel framework introduced in the context of the level-set method. This framework utilizes: discretizations that achieve a second-order accurate level-set method on non-graded adaptive Cartesian grids for solving the associated free boundary value problem for surface diffusion; and an established library for the partitioning of the grid. We consider the cases with: irreversible aggregation, which amounts to applying Dirichlet boundary conditions at the island boundary; and an asymmetric (Ehrlich-Schwoebel) energy barrier for attachment/detachment of atoms at the island boundary, which entails the use of a Robin boundary condition. We provide the scaling analyses performed on the Stampede supercomputer and numerical examples that illustrate the capability of our methodology to efficiently simulate different aspects of epitaxial growth. The combination of adaptivity and parallelism in our approach enables simulations that are several orders of magnitude faster than those reported in the recent literature and, thus, provides a viable framework for the systematic study of mound formation on crystal surfaces.

Updating QR factorization procedure for solution of linear least squares problem with equality constraints.

PubMed

Zeb, Salman; Yousaf, Muhammad

2017-01-01

In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.

Communications oriented programming of parallel iterative solutions of sparse linear systems

NASA Technical Reports Server (NTRS)

Patrick, M. L.; Pratt, T. W.

1986-01-01

Parallel algorithms are developed for a class of scientific computational problems by partitioning the problems into smaller problems which may be solved concurrently. The effectiveness of the resulting parallel solutions is determined by the amount and frequency of communication and synchronization and the extent to which communication can be overlapped with computation. Three different parallel algorithms for solving the same class of problems are presented, and their effectiveness is analyzed from this point of view. The algorithms are programmed using a new programming environment. Run-time statistics and experience obtained from the execution of these programs assist in measuring the effectiveness of these algorithms.

Model-based recursive partitioning to identify risk clusters for metabolic syndrome and its components: findings from the International Mobility in Aging Study

PubMed Central

Pirkle, Catherine M; Wu, Yan Yan; Zunzunegui, Maria-Victoria; Gómez, José Fernando

2018-01-01

Objective Conceptual models underpinning much epidemiological research on ageing acknowledge that environmental, social and biological systems interact to influence health outcomes. Recursive partitioning is a data-driven approach that allows for concurrent exploration of distinct mixtures, or clusters, of individuals that have a particular outcome. Our aim is to use recursive partitioning to examine risk clusters for metabolic syndrome (MetS) and its components, in order to identify vulnerable populations. Study design Cross-sectional analysis of baseline data from a prospective longitudinal cohort called the International Mobility in Aging Study (IMIAS). Setting IMIAS includes sites from three middle-income countries—Tirana (Albania), Natal (Brazil) and Manizales (Colombia)—and two from Canada—Kingston (Ontario) and Saint-Hyacinthe (Quebec). Participants Community-dwelling male and female adults, aged 64–75 years (n=2002). Primary and secondary outcome measures We apply recursive partitioning to investigate social and behavioural risk factors for MetS and its components. Model-based recursive partitioning (MOB) was used to cluster participants into age-adjusted risk groups based on variabilities in: study site, sex, education, living arrangements, childhood adversities, adult occupation, current employment status, income, perceived income sufficiency, smoking status and weekly minutes of physical activity. Results 43% of participants had MetS. Using MOB, the primary partitioning variable was participant sex. Among women from middle-incomes sites, the predicted proportion with MetS ranged from 58% to 68%. Canadian women with limited physical activity had elevated predicted proportions of MetS (49%, 95% CI 39% to 58%). Among men, MetS ranged from 26% to 41% depending on childhood social adversity and education. Clustering for MetS components differed from the syndrome and across components. Study site was a primary partitioning variable for all components except HDL cholesterol. Sex was important for most components. Conclusion MOB is a promising technique for identifying disease risk clusters (eg, vulnerable populations) in modestly sized samples. PMID:29500203

Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition

NASA Astrophysics Data System (ADS)

Parrish, Robert M.; Sherrill, C. David

2014-07-01

We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work through the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in systems with up to 220 atoms and 2845 basis functions.

Spatial assignment of symmetry adapted perturbation theory interaction energy components: The atomic SAPT partition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parrish, Robert M.; Sherrill, C. David, E-mail: sherrill@gatech.edu

2014-07-28

We develop a physically-motivated assignment of symmetry adapted perturbation theory for intermolecular interactions (SAPT) into atom-pairwise contributions (the A-SAPT partition). The basic precept of A-SAPT is that the many-body interaction energy components are computed normally under the formalism of SAPT, following which a spatially-localized two-body quasiparticle interaction is extracted from the many-body interaction terms. For electrostatics and induction source terms, the relevant quasiparticles are atoms, which are obtained in this work through the iterative stockholder analysis (ISA) procedure. For the exchange, induction response, and dispersion terms, the relevant quasiparticles are local occupied orbitals, which are obtained in this work throughmore » the Pipek-Mezey procedure. The local orbital atomic charges obtained from ISA additionally allow the terms involving local orbitals to be assigned in an atom-pairwise manner. Further summation over the atoms of one or the other monomer allows for a chemically intuitive visualization of the contribution of each atom and interaction component to the overall noncovalent interaction strength. Herein, we present the intuitive development and mathematical form for A-SAPT applied in the SAPT0 approximation (the A-SAPT0 partition). We also provide an efficient series of algorithms for the computation of the A-SAPT0 partition with essentially the same computational cost as the corresponding SAPT0 decomposition. We probe the sensitivity of the A-SAPT0 partition to the ISA grid and convergence parameter, orbital localization metric, and induction coupling treatment, and recommend a set of practical choices which closes the definition of the A-SAPT0 partition. We demonstrate the utility and computational tractability of the A-SAPT0 partition in the context of side-on cation-π interactions and the intercalation of DNA by proflavine. A-SAPT0 clearly shows the key processes in these complicated noncovalent interactions, in systems with up to 220 atoms and 2845 basis functions.« less

[Analytic methods for seed models with genotype x environment interactions].

PubMed

Zhu, J

1996-01-01

Genetic models with genotype effect (G) and genotype x environment interaction effect (GE) are proposed for analyzing generation means of seed quantitative traits in crops. The total genetic effect (G) is partitioned into seed direct genetic effect (G0), cytoplasm genetic of effect (C), and maternal plant genetic effect (Gm). Seed direct genetic effect (G0) can be further partitioned into direct additive (A) and direct dominance (D) genetic components. Maternal genetic effect (Gm) can also be partitioned into maternal additive (Am) and maternal dominance (Dm) genetic components. The total genotype x environment interaction effect (GE) can also be partitioned into direct genetic by environment interaction effect (G0E), cytoplasm genetic by environment interaction effect (CE), and maternal genetic by environment interaction effect (GmE). G0E can be partitioned into direct additive by environment interaction (AE) and direct dominance by environment interaction (DE) genetic components. GmE can also be partitioned into maternal additive by environment interaction (AmE) and maternal dominance by environment interaction (DmE) genetic components. Partitions of genetic components are listed for parent, F1, F2 and backcrosses. A set of parents, their reciprocal F1 and F2 seeds is applicable for efficient analysis of seed quantitative traits. MINQUE(0/1) method can be used for estimating variance and covariance components. Unbiased estimation for covariance components between two traits can also be obtained by the MINQUE(0/1) method. Random genetic effects in seed models are predictable by the Adjusted Unbiased Prediction (AUP) approach with MINQUE(0/1) method. The jackknife procedure is suggested for estimation of sampling variances of estimated variance and covariance components and of predicted genetic effects, which can be further used in a t-test for parameter. Unbiasedness and efficiency for estimating variance components and predicting genetic effects are tested by Monte Carlo simulations.

Partitioning Ocean Wave Spectra Obtained from Radar Observations

NASA Astrophysics Data System (ADS)

Delaye, Lauriane; Vergely, Jean-Luc; Hauser, Daniele; Guitton, Gilles; Mouche, Alexis; Tison, Celine

2016-08-01

2D wave spectra of ocean waves can be partitioned into several wave components to better characterize the scene. We present here two methods of component detection: one based on watershed algorithm and the other based on a Bayesian approach. We tested both methods on a set of simulated SWIM data, the Ku-band real aperture radar embarked on the CFOSAT (China- France Oceanography Satellite) mission which launch is planned mid-2018. We present the results and the limits of both approaches and show that Bayesian method can also be applied to other kind of wave spectra observations as those obtained with the radar KuROS, an airborne radar wave spectrometer.