ppxscal/embedding_network huggingface dataset:
Compared techniques for the critical submergence of an intake in water flow
Authors: Fikret Kocabas, Serap Unal
Venue: Advances in Engineering Software (2010)

Air-entraining vortex at intake is an important problem encountered in hydraulic engineering. Intake submergence depth could result in formation of the air-entraining free surface vortices. Unless the dangerous air entrainment is eliminated, air entraining causes mechanical damage, vibration in pipelines and loss of pump performance. The value of the intake's submergence when the vortex starts entraining air is known as ''critical submergence''. In this study, the critical submergence for a circular intake pipe in still-water and open channel flow for permeable and impermeable bottom was investigated. Experimental results were used to compare with critical spherical sink surface (CSSS), radial basis function based neural network (RBNN) and general linear model (GLM). The CSSS has the same center and discharge as the intake with the critical submergence. The GLM underlies most of the statistical analyses that are used in applied research. And the RBNN is one of the most used network models. The ranking of prediction on critical submergence is obtained as RBNN, GLM and CSSS, respectively.
Intelligent control of air traffic landing sequences
Authors: Q. A. Memon
Venue: International Journal of Modelling and Simulation (2008)

Due to a dramatic increase in air traffic around the globe, the tasks for air traffic controllers have increased multifold. This work aims to develop an air traffic control to prioritize landing sequences assigned to planes when, unexpectedly, a large number of planes approach the airfield. Two alternatives are proposed: one is based on rule-based expert system and another on artificial neural networks. The author shows that each of the models helps to optimize the prioritization of overall landing requests, with exception only to a situation of a larger number of emergencies. Further, a combination of these approaches is discussed to show that it does help in minimizing time to handle landing sequences during emergencies.
Kernel-based meshless methods
Authors: John Wallin, Thomas Wanner
Venue:  (2009)

In order to improve their applicability as a tool for solving partial differential equations in computational science, we equip kernel-based meshless methods with a number of new capabilities. First, we provide kernel-based meshless methods with the first wellposed, general technique which allows for adaptively-scaled trial functions. This is done by constructing an adaptively-scaled kernel which maintains positive definiteness. We extend sampling inequalities to optimally bound fractional order Sobolev norms in terms of possibly higher order data. This sampling inequality is then applied to obtain more optimal error bounds in a reformulation of Schaback&rsquo;s framework for unsymmetric meshless methods. We provide kernel-based meshless methods with a direct visualization technique, by adapting Fourier volume rendering to deal directly with meshless data, which was previously only used directly for grid-based data. Modern graphics hardware has emerged as a powerful architecture for scientific computing. We implement an unstructured grid-based inviscid, compressible flow solver on modern graphics hardware, and obtain an order of magnitude speed-up in comparison to an equivalent code running on a quad-core CPU. 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
Efficient construction of accurate multiple alignments and large-scale phylogenies
Authors: John D. Kececioglu, Michael J. Sanderson
Venue:  (2009)

A central focus of computational biology is to organize and make use of vast stores of molecular sequence data. Two of the most studied and fundamental problems in the field are sequence alignment and phylogeny inference. The problem of multiple sequence alignment is to take a set of DNA, RNA, or protein sequences and identify related segments of these sequences. Perhaps the most common use of alignments of multiple sequences is as input for methods designed to infer a phylogeny, or tree describing the evolutionary history of the sequences. The two problems are circularly related: standard phylogeny inference methods take a multiple sequence alignment as input, while computation of a rudimentary phylogeny is a step in the standard multiple sequence alignment method. Efficient computation of high-quality alignments, and of high-quality phylogenies based on those alignments, are both open problems in the field of computational biology. The first part of the dissertation gives details of my efforts to identify a best-of-breed method for each stage of the standard form-and-polish heuristic for aligning multiple sequences; the result of these efforts is a tool, called Opal, that achieves state-of-the-art 84.7% accuracy on the BAliBASE alignment benchmark. The second part of the dissertation describes a new algorithm that dramatically increases the speed and scalability of a common method for phylogeny inference called neighbor-joining; this algorithm is implemented in a new tool, called NINJA, which is more than an order of magnitude faster than a very fast implementation of the canonical algorithm, for example building a tree on 218,000 sequences in under 6 days using a single processor computer. 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
Polyphony, conflict and argumentation in networked and face-to-face exchanges among advanced english as a second language (esl) learners
Authors: Karen Adams
Venue:  (2009)

The goal of this study was to investigate through qualitative and quantitative constructs of analysis how 10 English as a Second Language students enrolled in an advanced writing course engaged in polyphony, conflict and argumentation during real-time, delayed and face-to-face (FTF) feedback exchanges. The emerging polyphony on these forums was embedded in the mismatch of salient cultural convictions, values, life experiences, and in the selection of highly controversial genres. Through the arguments of definition and evaluation students examined in their two papers, they instigated feedback dialogues where the impetus was placed on challenging feedback strategies, salient interrelational dynamics and the implementation of some of these strategies in their rough and final drafts. The delayed forums afforded opportunities for feedback strategies that were more confrontational than the real-time Collaboration Sessions and FTF encounters, where students were more cautious in their articulation of contradictory values. Such feedback exchanges also emerged within contradictory edifices: first, their instructor's expectation for devising demanding feedback strategies and the articulation of opposing views often contradicted students' need for maintaining friendly relationships with their peers. Second, the nexus between the intended outcome, i.e., scoring a higher grade, and students' role as reviewers were often contradictory since students, as reviewers, were expected to offer multiple suggestions, but, as authors, they often avoided contextualizing several strategies in their papers, especially counterarguments. Third, the unequal distribution of power between the instructor and students through the grading system often led students to solicit their instructor's assistance while avoiding contextualizing several of their peers' strategies in an attempt to improve their grades. In terms of qualitative analysis, Chi-square, X2, measures indicated that there were no statistically significant differences in the number of proposed or implemented strategies in a particular forum. However, Chi-square tests administered to examine 3 out of the 5 categories under which all strategies were classified, (1) criteria [CR], (2) clarifications/elaborations [C/E], (3) counterarguments [CA], (4) research [R] and (5) other strategies [O], indicated that the number of instigated and proposed criteria was higher on the Collaboration Sessions, while the number of proposed clarifications/elaborations was higher than the other strategies, i.e. counterarguments. 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 meta-analysis of two-dimensional electrophoresis pattern of the Parkinson's disease-related protein DJ-1
Authors: Massimo Natale, Dario Bonino, Paolo Consoli, Tiziana Alberio, Rivka G. Ravid, Mauro Fasano, Enrico M. Bucci
Venue: Bioinformatics (2010)

Motivation: The two-dimensional electrophoresis (2-DE) pattern of proteins is thought to be specifically related to the physiological or pathological condition at the moment of sample preparation. On this ground, most proteomic studies move to identify specific hallmarks for a number of different conditions. However, the information arising from these investigations is often incomplete due to inherent limitations of the technique, to extensive protein post-translational modifications and sometimes to the paucity of available samples. The meta-analysis of proteomic data can provide valuable information pertinent to various biological processes that otherwise remains hidden. Results: Here, we show a meta-analysis of the PD protein DJ-1 in heterogeneous 2-DE experiments. The protein was shown to segregate into specific clusters associated with defined conditions. Interestingly, the DJ-1 pool from neural tissues displayed a specific and characteristic molecular weight and isoelectric point pattern. Moreover, changes in this pattern have been related to neurodegenerative processes and aging. These results were experimentally validated on human brain specimens from control subjects and PD patients. Availability: ImageJ is a public domain image processing program developed by the National Institutes of Health and is freely available at http://rsbweb.nih.gov/ij. All the ImageJ macros used in this study are available as supplementary material and upon request at info@biodigitalvalley.com. XLSTAT can be purchased online at http://www.xlstat.com/en/home/ at a current cost of ~300 EUR. Contact: enrico.bucci@biodigitalvalley.com 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
Multilevel minimum cross entropy threshold selection based on the honey bee mating optimization
Authors: Ming-Huwi Horng
Venue: Expert Systems with Applications: An International Journal (2010)

Image thresholding is an important technique for image processing and pattern recognition. Many thresholding techniques have been proposed in the literature. Among them, the minimum cross entropy thresholding (MCET) has been widely applied. In this paper, a new multilevel MCET algorithm based on the technology of the honey bee mating optimization (HBMO) is proposed. Three different methods included the exhaustive search, the particle swarm optimization (PSO) and the quantum particle swarm optimization (QPSO) methods are also implemented for comparison with the results of the proposed method. The experimental results manifest that the proposed HBMO-based MCET algorithm can efficiently search for multiple thresholds which are very close to the optimal ones examined by the exhaustive search method. In comparison with the other two thresholding methods, the segmentation results using the HBMO-based MCET algorithm is the best. Furthermore, the convergence of the HBMO-based MCET algorithm can rapidly achieve, and the results are validated that the proposed HBMO-based MCET algorithm is efficient.
The solution of multipoint boundary value problems by the Optimal Homotopy Asymptotic Method
Authors: Javed Ali, S. Islam, Sirajul Islam, Gul Zaman
Venue: Computers Mathematics with Applications (2010)

In this work, we solve multipoint boundary value problems using the Optimal Homotopy Asymptotic Method (OHAM).The proposed method is tested upon several problems from the literature and the results are compared with the available exact solution. This method provides easy tools to control the convergence region of approximating solution series where ever necessary.
On the α-migrativity of semicopulas, quasi-copulas, and copulas
Authors: R. Mesiar, H. Bustince, J. Fernandez
Venue: Information Sciences: an International Journal (2010)

In this paper we address the problem of @a-migrativity (for a fixed @a) for semicopulas, copulas and quasi-copulas. We introduce the concept of an @a-sum of semicopulas. This new concept allows us to completely characterize @a-migrative semicopulas and copulas. Moreover, @a-sums also provide a means to obtain a partial characterization of @a-migrative quasi-copulas.
Efficient motor control learning
Authors: Stuart J. Russell
Venue:  (2009)

There are many challenges to learning optimal motor control. These challenges include noisy environments and sensors, nonlinear dynamics, continuous variables, high-dimensional problem domains, and redundancy. Reinforcement learning can be used, in principle, to find optimal controllers; however, the traditional learning algorithms are often too slow because obtaining training data is expensive. Although policy gradient methods have shown some promising results, they are limited by the rate at which they can estimate the gradient of the objective function with respect to a given policy's parameters. These algorithms typically estimate the gradient from a number of policy trials. In the noisy setting, however, many policy trials may be necessary to achieve a desired level of performance. This dissertation presents techniques that may be used to minimize the total number of trials required. The main difficulty arises because each policy trial returns a noisy estimate of the performance measure. As a result, we have noisy gradient estimates. One source of noise is caused by the use of randomized policies (often used for exploration purposes). We use response surface models to predict the effect that this noise has on the observed performance. This allows us to reduce the variance of the gradient estimates, and we derive expressions for the minimal-variance model for a variety of problem settings. Other sources of noise come from the environment and from the agent's actuators. Sensor data, which partially measures the effect of this noise, can be used to explain away the noise-induced perturbations in the expected performance. We show how to incorporate the sensor information into the gradient estimation task, further reducing the variance of the gradient estimates. In addition, we show that useful sensor encodings have the following properties: the sensor data is uncorrelated with the agent's choice of action and the sensor data is correlated with the perturbations in performance. Finally, we demonstrate the effectiveness of our approach by learning controllers for a simulated dart thrower and quadruped locomotion task. 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
Some delay integral inequalities on time scales
Authors: Wei Nian Li
Venue: Computers Mathematics with Applications (2010)

In this paper, using Gronwall's inequality, we investigate some delay integral inequalities on time scales, which provide explicit bounds on unknown functions. Our results unify and extend some delay integral inequalities and their corresponding discrete analogues. The inequalities given here can be used as tools in the qualitative theory of certain classes of delay dynamic equations on time scales.
Technical communique: A Zakai equation derivation of the extended Kalman filter
Authors: Robert J. Elliott, Simon Haykin
Venue: Automatica (Journal of IFAC) (2010)

A discrete time filter is considered where both the observation and signal process have non-linear dynamics with additive Gaussian noise. Using the reference probability framework a convolution type Zakai equation is obtained which updates the unnormalized conditional density. Using first order approximations this equation can be solved recursively and the extended Kalman filter can be derived.
Defining and controlling the heterogeneity of a cluster: The Wrekavoc tool
Authors: Louis-Claude Canon, Olivier Dubuisson, Jens Gustedt, Emmanuel Jeannot
Venue: Journal of Systems and Software (2010)

The experimental validation and the testing of solutions that are designed for heterogeneous environments are challenging. We introduce Wrekavoc as an accurate tool for this purpose: it runs unmodified applications on emulated multi-site heterogeneous platforms. Its principal technique consists in downgrading the performance of the platform characteristics in a prescribed way. The platform characteristics include the compute nodes themselves (CPU and memory) and the interconnection network for which a controlled overlay network above the homogeneous cluster is built. In this article we describe the tool, its performance, its accuracy and its scalability. Results show that Wrekavoc is a very versatile tool that is useful to perform high-quality experiments (in terms of reproducibility, realism, control, etc.).
LMCGrid: a low management cost grid computation model
Authors: Y. Yang, X. Yang, C. Zhou
Venue: International Journal of Computers and Applications (2008)

This paper proposes a Low Management Cost computing Grid model (LMCGrid), aiming at harvesting the idle time of computers connected to Internet to run large-scale distributed applications. In LMCGrid, no specific node is designated to manage dynamically changing resources. Despite the absence of the management node, the corresponding information mechanism, task scheduling algorithm and limited task duplicating algorithm naturally evolve the system into equilibrium to perform large-scale distributed computation with low cost. A simulation software package has been developed to verify this model and to assess its performance. The results showed that LMCGrid reasonably distributed loads in a dynamic environment, and fully utilized the computational capacity of idling resources, and that it was feasible to solve large-scale, embarrassingly parallel applications such as parameter sweep and Monte Carlo simulations efficiently.
The search for potentially interesting products in an e-marketplace: An agent-to-agent argumentation approach
Authors: Shiu-Li Huang, Chia-Yin Lin
Venue: Expert Systems with Applications: An International Journal (2010)

In existing e-marketplaces, buyers use search engines to specify conditions and to find products that match those conditions exactly. However, some products that may be potentially interesting to buyers are nearly impossible to find. This research aims to design a multi-agent e-marketplace in which buyers and sellers delegate agents to argue about products via an argumentation mechanism. This mechanism enables sellers to persuade buyers to consider purchasing products; it also helps buyers in their search for potentially interesting products. This research adopts Semantic Web technology to express agents' ontologies and proposes an information-gathering approach that supports argumentation. A prototype was developed and a laboratory experiment was conducted to assess the approach's performance. The experimental results show that the proposed mechanism is able to help buyers search for both exactly and potentially interesting products. The study also explores the reasons why searching for potentially interesting products is crucial to e-marketplaces. The proposed prototype and its attendant approach can inspire both existing and initiative e-marketplaces to design advanced product searching and recommendation mechanisms.
When self-pacing goes wrong: a comparison of two methods for reducing computer-based racing
Authors: Alyce M. Dickinson
Venue:  (2009)

Self-pacing, although often seen as one of the primary benefits of computer-based instruction (CBI), can also result in an important problem, namely, computer-based racing. Computer-based racing is when learners respond so quickly within CBI that mistakes are made, even on well-known material. This study compared traditional CBI with two forms of CBI designed to reduce computer-based racing: incentives/disincentives and postfeedback delays. All three formats were evaluated in terms of both performance and satisfaction using a between group repeated measures design with pretest and posttest. Dependent measures included posttest scores, satisfaction questionnaire ratings, percentage correct during learning, and total training time. Posttest scores favored the use of postfeedback delays to improve learning over incentives/disincentives and control conditions. Postfeedback delays negatively affected satisfaction in comparison to the control condition, although no satisfaction differences were found between incentives/disincentives and postfeedback delays. 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
An adaptive single-hop medium access control layer for noisy channels
Authors: John A. Hamilton,  Jr.
Venue:  (2009)

The work presented in this dissertation is for a contribution to the data link layer and its responsibility of managing the physical channel in a mobile ad-hoc network (MANET). Wireless networks in general are susceptible to noise in the spectrum, which can result in low throughput, loss of critical resources, and high re-transmission rates at the physical and link layers. As a result, there is a growing need for wireless technology that can continue to operate in the presence of noise. A mathematical algorithm has recently been developed which uses concurrent and super-imposed codes, which when applied to wireless communications allows for jam-resistant communications without a pre-shared secret. By leveraging this algorithm, the research for this dissertation will create a jam-resistant single-hop medium access control (MAC) protocol that adapts to the level of noise in the channel. The protocol will dynamically adjust the parameters for encoding to overcome the varying levels of interference. The new protocol will allow for communications to continue in the presence of noise or jamming attacks. 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
Brief paper: Identification for robust H2 deconvolution filtering
Authors: Xavier Bombois, Håkan Hjalmarsson, Gérard Scorletti
Venue: Automatica (Journal of IFAC) (2010)

This paper addresses robust deconvolution filtering when the system and noise dynamics are obtained by parametric system identification. Consistent with standard identification methods, the uncertainty in the estimated parameters is represented by an ellipsoidal uncertainty region. Three problems are considered: (1) computation of the worst case H"2 performance of a given deconvolution filter in this uncertainty set; (2) design of a filter which minimizes the worst case H"2 performance in this uncertainty set; (3) input design for the identification experiment, subject to a limited input power budget, such that the filter in (2) gives the smallest possible worst case H"2 performance. It is shown that there are convex relaxations of the optimization problems corresponding to (1) and (2) while the third problem can be treated via iterating between two convex optimization problems.