ppxscal/embedding_network huggingface dataset:
Statistical methods for genetic association mapping of complex traits with related individuals
Authors: Mary Sara Mcpeek
Venue:  (2009)

We develop statistical methods to address both dependent and partially-observed data and apply these methods to problems in haplotype-based association analysis of complex traits in related individuals. We consider a general setting in which the complete data are dependent with marginal distributions following a generalized linear model. We form a vector Z whose elements are conditional expectations of the elements of the complete-data vector, given selected functions of the incomplete data. Assuming that the covariance matrix of Z is available, we form an optimal linear estimating function based on Z, which we solve by an iterative method. This approach allows us to address key difficulties in the haplotype frequency estimation and testing problems in related individuals: (1) dependence that is known but can be complicated; (2) data that are incomplete for structural reasons, as well as possibly missing, with different amounts of information for different observations; (3) the need for computational speed in order to analyze large numbers of markers; (4) a well-established null model, but an alternative model that is unknown and is problematic to fully specify in related individuals. We apply the method to test for association of haplotypes with alcoholism in the GAW 14 COGA data set. We then address the problem of testing for association with untyped variants. Current genome-wide association studies only genotype a subset of all genomic variants. However, many of the untyped variants can be well-predicted from typed variants, with information on the joint distribution of typed and untyped variants available from an external reference panel such as HapMap. Incorporation of such external information can allow one to perform tests of association between untyped variants and phenotype, thereby making more efficient use of the available genotype data. We introduce a new method, ATRIUM, to test for association between untyped SNPs and phenotype, based on genome screen data in case-control samples in which some individuals are related. ATRIUM uses information from an external reference panel to specify a direction in which to perform a 1-df test of association with an untyped SNP. It properly accounts for uncertainty in haplotype information based on unphased genotype data and for dependence of genotypes across related individuals. We demonstrate that ATRIUM is robust in that it maintains the nominal type I error rate even when the external reference sample is not well-matched to the case-control sample. We apply the method to detect association between type 2 diabetes and variants on chromosome 10 in the Framingham SHARe data. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A new heuristic approach for non-convex optimization problems
Authors: R. Toscano, P. Lyonnet
Venue: Information Sciences: an International Journal (2010)

In this work a new optimization method, called the heuristic Kalman algorithm (HKA), is presented. This new algorithm is proposed as an alternative approach for solving continuous, non-convex optimization problems. The principle of HKA is to explicitly consider the optimization problem as a measurement process designed to give an estimate of the optimum. A specific procedure, based on the Kalman estimator, was developed to improve the quality of the estimate obtained through the measurement process. The main advantage of HKA, compared to other metaheuristics, lies in the small number of parameters that need to be set by the user. Further, it is shown that HKA converges almost surely to a near-optimal solution. The efficiency of HKA was evaluated in detail using several non-convex test problems, both in the unconstrained and constrained cases. The results were then compared to those obtained via other metaheuristics. The numerical experiments show that HKA is a promising approach for solving non-convex optimization problems, particularly in terms of computation time and success ratio.
Almost periodic solutions for an impulsive delay Nicholson's blowflies model
Authors: Jehad O. Alzabut
Venue: Journal of Computational and Applied Mathematics (2010)

By means of the contraction mapping principle and Gronwall-Bellman's inequality, we prove the existence and exponential stability of positive almost periodic solution for an impulsive delay Nicholson's blowflies model. The main results are illustrated by an example.
Multiplayer games over Vehicular Ad Hoc Networks: A new application
Authors: Ozan K. Tonguz, Mate Boban
Venue: Ad Hoc Networks (2010)

In this paper we investigate the possibility of a new type of application, namely multiplayer games, in a Vehicular Ad Hoc Network (VANET) environment. First, we analyze the available empirical data on travel and traffic volume in the United States, and point out the most important challenges that have to be met in order to enable multiplayer games over VANET. We then propose a new paradigm of multiplayer games over VANET, one which utilizes the new, interactive and dynamic VANET environment, while adapting to its inherent constraints.
Symmetry parameters for 3D pattern classification
Authors: Frédérique Robert-Inacio
Venue: Pattern Recognition Letters (2005)

The Winternitz's parameter enables to evaluate a symmetry degree for a given 2D convex body, with respect to a particular point. This point is the best-centered point according to symmetry criteria. The generalization of this parameter in 3D is studied and a second 3D-parameter is derived from the 2D-Winternitz's parameter.
Management of evolving semantic grid metadata within a collaborative platform
Authors: Michael Hartung, Frank Loebe, Heinrich Herre, Erhard Rahm
Venue: Information Sciences: an International Journal (2010)

Grid environments, providing distributed infrastructures, computing resources and data storage, usually show a high degree of heterogeneity and change in their metadata. We propose a platform for collaborative management and maintenance of common metadata for grids. As the conceptual foundation of this platform, a meta model is presented which distinguishes structured descriptions and classification structures that both are modifiable. On this basis, the system allows for the creation and editing of grid relevant metadata and provides various search and navigation facilities for grid participants. We applied the platform to the German D-Grid initiative by establishing the D-Grid Ontology (DGO).
GOSemSim
Authors: Guangchuang Yu, Fei Li, Yide Qin, Xiaochen Bo, Yibo Wu, Shengqi Wang
Venue: Bioinformatics (2010)

Summary: The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters. Four information content (IC)-and a graph-based methods are implemented in the GOSemSim package, multiple species including human, rat, mouse, fly and yeast are also supported. The functions provided by the GOSemSim offer flexibility for applications, and can be easily integrated into high-throughput analysis pipelines. Availability: GOSemSim is released under the GNU General Public License within Bioconductor project, and freely available at http://bioconductor.org/packages/2.6/bioc/html/GOSemSim.html Contact:boxc@bmi.ac.cn; sqwang@bmi.ac.cn Supplementary information: Supplementary information is available at Bioinformatics online. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A class of integral approximations for the factorial function
Authors: Cristinel Mortici
Venue: Computers Mathematics with Applications (2010)

We introduce Stirling's formula in a more general class of approximation formulas to extend the integral representation of Liu [Z. Liu, A new version of the Stirling formula, Tamsui Oxf. J. Math. Sci. 23 (4) (2007) 389-392]. Finally, an accurate approximation for the factorial function is established.
Short communication: A comment on modified big-M method to recognize the infeasibility of linear programming models
Authors: Gholam R. Amin
Venue: Knowledge-Based Systems (2010)

Recently Soleimani-Damaneh (modified big-M method to recognize the infeasibility of linear programming models, Knowledge-Based Systems 21 (2008) 377-382), proposed a modified big-M method for detecting the infeasibility of a linear programming problem. This note discusses on the essential theorem given in the mentioned study and gives the required assumption for distinguishing the infeasibility of an LP model using the big-M method.
Fast convergence to network fairness
Authors: Ageliki Tsioliaridou, Vassilis Tsaoussidis
Venue: Journal of Systems and Software (2010)

Most AQM algorithms, such as RED, assure fairness through randomness in congestion notification. However, randomness results in fair allocation of network resources only when time limitations are not considered. This is not compatible with the current Internet, where traffic oscillations are frequent and the demand for fair treatment is rather urgent, due to short duration of most applications. Given the short duration of most modern Internet applications, fast convergence to fairness is necessitated. In this paper, we use fairness as the major criterion to adjust traffic and present a corresponding algorithm of active queue management, which is called Explicit Global Congestion Notifier (EGCN). EGCN notifies flows almost simultaneously about incipient congestion by marking packets arriving at the router's queue, when the load in the network increases and buffer overflow is expected. This is a new approach compared with the random notification policy of RED or ECN. EGCN distributes the burden to adjust backward to more flows and consequently allows for smoother window adjustments. We elaborate on the properties of system-wide response in terms of fairness, smoothness and efficiency. Simulation results demonstrate a clear-cut advantage of the proposed scheme.
A model for estimating the performance of synchronous parallel network simulation
Authors: X. Wang, B. Fang, H. Zhang, W. Zhang
Venue: International Journal of Modelling and Simulation (2008)

This paper describes a model for estimating the performance of synchronous network simulation. The model is developed based on the BSP model, and includes various factors that may affect the performance of synchronous network simulation, such as load balancing, communication overhead, lookahead, and hardware platforms for running simulation. The model can not only predict but also help to improve the performance of synchronous network simulation. Experiments show that the model can estimate performance exactly. Treating the model as an objective function when the network topology is partitioned for synchronous simulation efficiently improves the performance of synchronous network simulation.
Exclusive disjunctive soft sets
Authors: Zhi Xiao, Ke Gong, Sisi Xia, Yan Zou
Venue: Computers Mathematics with Applications (2010)

Soft sets theory, initiated by Molodtsov, is an emerging tool to deal with uncertain problems and has been studied by scholars in both theory and practice. This paper proposes the notion of exclusive disjunctive soft sets and studies some of its operations, such as, restricted/relaxed AND operations, dependency between exclusive disjunctive soft sets and bijective soft sets, exclusive disjunctive soft decision systems, reduction of exclusive disjunctive soft decision systems, core of exclusive disjunctive soft decision systems, decision rules in exclusive disjunctive decision soft sets. Moreover, this study gives an application of exclusive disjunctive soft sets, which shows that it can be applied to attribute reduction of incomplete information system.
Standard virtual biological parts
Authors: M. T. Cooling, V. Rouilly, G. Misirli, J. Lawson, T. Yu, J. Hallinan, A. Wipat
Venue: Bioinformatics (2010)

Motivation: Fabrication of synthetic biological systems is greatly enhanced by incorporating engineering design principles and techniques such as computer-aided design. To this end, the ongoing standardization of biological parts presents an opportunity to develop libraries of standard virtual parts in the form of mathematical models that can be combined to inform system design. Results: We present an online Repository, populated with a collection of standardized models that can readily be recombined to model different biological systems using the inherent modularity support of the CellML 1.1 model exchange format. The applicability of this approach is demonstrated by modeling gold-medal winning iGEM machines. Availability and Implementation: The Repository is available online as part of http://models.cellml.org. We hope to stimulate the worldwide community to reuse and extend the models therein, and contribute to the Repository of Standard Virtual Parts thus founded. Systems Model architecture information for the Systems Model described here, along with an additional example and a tutorial, is also available as Supplementary information. The example Systems Model from this manuscript can be found at http://models.cellml.org/workspace/bugbuster. The Template models used in the example can be found at http://models.cellml.org/workspace/SVP_Templates200906. Contact: m.cooling@auckland.ac.nz Supplementary information:Supplementary data are available at Bioinformatics online. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
A symbolic fault-prediction model based on multiobjective particle swarm optimization
Authors: André B. de Carvalho, Aurora Pozo, Silvia Regina Vergilio
Venue: Journal of Systems and Software (2010)

In the literature the fault-proneness of classes or methods has been used to devise strategies for reducing testing costs and efforts. In general, fault-proneness is predicted through a set of design metrics and, most recently, by using Machine Learning (ML) techniques. However, some ML techniques cannot deal with unbalanced data, characteristic very common of the fault datasets and, their produced results are not easily interpreted by most programmers and testers. Considering these facts, this paper introduces a novel fault-prediction approach based on Multiobjective Particle Swarm Optimization (MOPSO). Exploring Pareto dominance concepts, the approach generates a model composed by rules with specific properties. These rules can be used as an unordered classifier, and because of this, they are more intuitive and comprehensible. Two experiments were accomplished, considering, respectively, fault-proneness of classes and methods. The results show interesting relationships between the studied metrics and fault prediction. In addition to this, the performance of the introduced MOPSO approach is compared with other ML algorithms by using several measures including the area under the ROC curve, which is a relevant criterion to deal with unbalanced data.
Rational bases for convex polyhedra
Authors: E. Wachspress
Venue: Computers Mathematics with Applications (2010)

In Wachspress (1975) [2] rational bases were constructed for convex polyhedra whose vertices were all of order three. The restriction to order three was first removed by Warren (1996) [3] and his analysis was refined subsequently by Warren and Schaefer (2004) [4]. A new algorithm (GADJ) for finding the denominator polynomial common to all the basis functions was exposed in Dasgupta and Wachspress (2007) [1] for convex polyhedra with all vertices of order three. This algorithm is applied here for generating bases for general convex polyhedra.
Agent formations in 3D spaces with communication limitations using an adaptive Q-structure
Authors: Shuzhi Sam Ge, Cheng-Heng Fua, Khiang Wee Lim
Venue: Robotics and Autonomous Systems (2010)

In this article, we further extend the Queue-formation structure (or Q-structure) in 3D spaces with additional features including: (i) specifying orientation information, (ii) a mechanism for forming sub-formations before the convergence into the final formation, and (iii) adapting the communication structure when communications are limited. The virtual Bobber-agents are used to guide each vehicle toward the appropriate queue, by acting as intermediate targets. In addition, virtual constellation-agents bias the motion of each vehicle to within a user-defined cone to the front of the vehicle so that abrupt direction changes are avoided as far as possible. The proposed scheme relies mainly on simple behaviors between embodied and virtual agents and is computationally inexpensive method. Extensive simulations show the effectiveness of the proposed method.
Strategic design of competing centralized supply chain networks for markets with deterministic demands
Authors: Shabnam Rezapour, Reza Zanjirani Farahani
Venue: Advances in Engineering Software (2010)

This paper develops an equilibrium model to design a centralized supply chain network operating in markets under deterministic price-depended demands and with a rival chain present. The two chains provide competitive products, either identical or highly substitutable, for some participating retailer markets. We model the optimizing behavior of these two chains, derive the equilibrium conditions, and establish the finite-dimensional variational inequality formulation, and solve it using a modified projection method. We provide properties of the equilibrium pattern in terms of the existence and uniqueness results. Our model also considers the impacts of the strategic facility location decisions on the tactical inventory and shipment decisions. Finally, we illustrate the model through a numerical example and discuss how the prices, costs, incomes, and profits behave with respect to key marketing activities, such as advertising, brand positioning, and brand loyalty.
Using data mining techniques to automatically construct concept maps for adaptive learning systems
Authors: Shyi-Ming Chen, Shih-Ming Bai
Venue: Expert Systems with Applications: An International Journal (2010)

It is obvious that to construct concept maps for providing the learning guidance to learners is an important research topic of adaptive learning systems. Because the existing method to construct concept maps only considers the association rules that questions are not correctly answered, it will miss some information about questions that are correctly answered by the learners. Moreover, the existing method also has the drawback that it will build unnecessary relationships or lose some relationships between concepts in the constructed concept maps. In this paper, we present a new method to automatically construct concept maps based on data mining techniques for adaptive learning systems. The proposed method can overcome the drawbacks of the existing method. It provides us a useful way to automatically construct concept maps in adaptive learning systems.
Learning grasping points with shape context
Authors: Jeannette Bohg, Danica Kragic
Venue: Robotics and Autonomous Systems (2010)

This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.
Brief paper: Least squares based iterative identification for a class of multirate systems
Authors: Xinggao Liu, Jing Lu
Venue: Automatica (Journal of IFAC) (2010)

This paper studies modeling and identification problems for multi-input multirate systems with colored noises. The state-space models are derived for the systems with different input updating periods and furthermore the corresponding transfer functions are obtained. To solve the difficulty of identification models with unmeasurable noises terms, the least squares based iterative algorithm is presented by replacing the unmeasurable variables with their iterative estimates. Finally, the simulation results indicate that the proposed iterative algorithm has advantages over the recursive algorithms.
Predicting service request rates for adaptive resource allocation in SOA
Authors: Alexander Serebrenik, Natalia Sidorova
Venue: Proceedings of the International Workshop on Enterprises & Organizational Modeling and Simulation (2009)

Service orientation is rapidly becoming the common practice in the IT world. A price one often has to pay for the advantages of service oriented architectures (SOA) is performance deterioration. SOA performance heavily depends on the allocation of computational resources to services. The needs of services in computational resources are however changing, depending e.g. on the environmental factors and changes in business processes (and hence service orchestrations). To ensure good performance results, the resource allocation should respond to the changes in the SOA environment. In this paper we focus on the detection of the changes in the environment and the prediction of the expected service requests rates. For this purpose we first discover a stochastic model of the service request rates. Then we monitor the system to detect changes in the environment behaviour and signal the necessity to reconsider the resource allocation, providing a prediction of the service request rates for the coming period. Moreover, we monitor whether the model is still a fair reflection of the behaviour, and when necessary, we adapt the model appropriately.
A multi-path routing scheme for torus-based NOCs
Authors: Y. Jiao, Y. Yang, M. Yang, Y. Jiang
Venue: International Journal of Computers and Applications (2008)

In Networks-on-Chip (NoC) designs, crosstalk noise has become a serious issue which may cause the communication channel unreliable. The crosstalk problem can be mitigated by wide spacing of serial lines. However, the wider spacing of serial lines will reduce the number of the lines, thus reduce the data throughput. In this paper, a new fully adaptive multi-path routing (MPR) scheme is proposed to maximize the data throughput by utilizing multiple paths for concurrent data transmission. For the proposed MPR algorithm, two transport models are considered: the full-wire-bank transport model (FM) and the half-wire-bank transport model (HM). Theoretical analysis shows that the MPR scheme under both FM and HM achieves improvement in data throughput when single pair of nodes are in communication. When multiple pairs of nodes are in communication, simulation results demonstrate that the MPR scheme under FM significantly improves the normalized accepted traffic and throughput as well as average message latency than the YX routing algorithm in most network loads.