ppxscal/embedding_network huggingface dataset:
A methodology for the development of discrete adjoint solvers using automatic differentiation tools
Authors: A. C. Marta, C. A. Mader, J. R. R. A. Martins, E. Van der Weide, J. J. Alonso
Venue: International Journal of Computational Fluid Dynamics (2007)

A methodology for the rapid development of adjoint solvers for computational fluid dynamics (CFD) models is presented. The approach relies on the use of automatic differentiation (AD) tools to almost completely automate the process of development of discrete adjoint solvers. This methodology is used to produce the adjoint code for two distinct 3D CFD solvers: a cell-centred Euler solver running in single-block, single-processor mode and a multi-block, multi-processor, vertex-centred, magneto-hydrodynamics (MHD) solver. Instead of differentiating the entire source code of the CFD solvers using AD, we have applied it selectively to produce code that computes the transpose of the flux Jacobian matrix and the other partial derivatives that are necessary to compute sensitivities using an adjoint method. The discrete adjoint equations are then solved using the Portable, Extensible Toolkit for Scientific Computation (PETSc) library. The selective application of AD is the principal idea of this new methodology, which we call the AD adjoint (ADjoint). The ADjoint approach has the advantages that it is applicable to any set of governing equations and objective functions and that it is completely consistent with the gradients that would be computed by exact numerical differentiation of the original discrete solver. Furthermore, the approach does not require hand differentiation, thus avoiding the long development times typically required to develop discrete adjoint solvers for partial differential equations, as well as the errors that result from the necessary approximations used during the differentiation of complex systems of conservation laws. These advantages come at the cost of increased memory requirements for the discrete adjoint solver. However, given the amount of memory that is typically available in parallel computers and the trends toward larger numbers of multi-core processors, this disadvantage is rather small when compared with the very significant advantages that are demonstrated. The sensitivities of drag and lift coefficients with respect to different parameters obtained using the discrete adjoint solvers show excellent agreement with the benchmark results produced by the complex-step and finite-difference methods. Furthermore, the overall performance of the method is shown to be better than most conventional adjoint approaches for both CFD solvers used.
Measuring the Complexity of Traces Using Shannon Entropy
Authors: Abdelwahab Hamou-Lhadj
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

Exploring the content of large execution traces can be a tedious task without efficient tool support. Building efficient trace analysis tools, however, requires a good understanding of the complexity embedded in traces. Trace complexity has traditionally been measured using the file size or the number of lines in the trace. In this paper, we argue that these metrics provide limited indication of the effort required to understand the content of a trace. We address this issue by introducing new trace complexity metrics based on the concept of entropy. Our metrics measure two important aspects of an execution trace: repeatability and variability. We present a case study where we apply the metrics to several execution traces. A discussion on how we can reduce the complexity of a trace based on these metrics is also presented.
A Las Vegas algorithm for linear programming when the dimension is small
Authors: K. L. Clarkson
Venue: Proceedings of the 29th Annual Symposium on Foundations of Computer Science (1988)

An algorithm for solving linear programming problems is given. The expected number of arithmetic operations required by the algorithm is given. The expectation is with respect to the random choices made by the algorithm, and the bound holds for any given input. The technique can be extended to other convex programming problems.
UTR-Tree: An Index Structure for the Full Uncertain Trajectories of Network-Constrained Moving Objects
Authors: Zhiming Ding
Venue: Proceedings of the The Ninth International Conference on Mobile Data Management (2008)

The uncertainty management problem for moving objects databases has been well studied recently, with many models and algorithms proposed. However, very limited work has dealt with the index of uncertain trajectories for a running moving objects database. In this paper, we propose an index framework, the UTR-Tree, for indexing the full uncertain trajectories of network constrained moving objects. Through a dynamic index maintenance technique which is associated with location updates, the UTR-Tree can deal with the full uncertain trajectories, which include not only the historical locations of moving objects, but also their current and near future location information with uncertainty considered, so that the queries on the whole life span of the moving objects can be efficiently supported. The experimental results show that the UTR-Tree outperforms previously proposed network-based moving object index methods in dealing with full uncertain trajectories.
Unequal weighting for improved positioning in GPS-less sensor networks
Authors: Thomas Haenselmann, Marcel Busse, Thomas King, Wolfgang Effelsberg
Venue: EURASIP Journal on Advances in Signal Processing (2008)

Positioning can be done by means of triangulation in which triples of position-aware nodes estimate a neighbor's position with the help of distances. If a larger number of nodes exist, multiple position estimates can be averaged to yield a more precise mean position. Rather than applying equal weights to each position estimate, we propose an unequal weighting scheme which emphasizes those summands in the averaging process that are more reliable than others. We will show that significant improvements of the overall estimate can be achieved, given that additional information about the error variance of a contributing estimate is known. A major advantage of the approach is that the precision of existing positioning systems can be improved without technical modifications.
Application-Oriented Distributed Sensor Network
Authors: P. Mariño, F. P. Fontán, M. A. Domínguez, S. Otero
Venue: Proceedings of the Third International Conference on Systems (2008)

Biological research in agriculture needs a lot of specialized electronic sensors in order to fulfill different goals, like as: climate monitoring, soil and fruit assessment, control of insects and diseases, chemical pollutants, identification and control of weeds, crop tracking, and so on. That research must be supported by consistent biological models able to simulate diverse environmental conditions, in order to predict the right human actions before risky biological damage could be irreversible. In this paper is described an experimental distributed network based on climatic an biological wireless sensors, for providing real measurements in order to validate different biological models used for viticulture applications. Firstly is introduced the experimental network for field automatic data acquisition, as a system based in a distributed process. Following, the design of the wireless network is explained in detail, with a previous discussion about the state-of-the-art, and some measurements for viticulture research are pointed out. Finally future developments are stated.
Using backpropagation neural network for face recognition with 2D+3D hybrid information
Authors: Te-Hsiu Sun, Fang-Chih Tien
Venue: Expert Systems with Applications: An International Journal (2008)

Biometric measurements received an increasing interest for security applications in the last two decades. After the 911 terrorist attacks, face recognition has been an active research in this area. However, very few research group focus on face recognition from both 2D and 3D facial images. Almost all existing recognition systems rely on a single type of face information: 2D intensity (or color) image or 3D range data set [Wang, Y., Chua, C., & Ho, Y. (2002). Facial feature detection and face recognition from 3D and 3D images. Pattern Recognition Letters, 23, 1191-1202]. The objective of this study is to develop an effective face recognition system that extracts and combines 2D and 3D face features to improve the recognition performance. The proposed method derived the information of 3D face (disparity face) using a designed synchronous Hopfield neural network. Then, we retrieved 2D and 3D face features with principle component analysis (PCA) and local autocorrelation coefficient (LAC) respectively. Eventually, the information of features was learned and classified using backpropagation neural networks. An experiment was conducted with 100 subjects, and for each subject thirteen stereo face images were taken with different expressions. Among them, seven faces with expressions were used for training, and the rest of the expressions were used for testing. The experimental results show that the proposed method effectively improved the recognition rate by combining the 2D with 3D face information.
A Greedy Two-stage Gibbs Sampling Method for Motif Discovery in Biological Sequences
Authors: Li-fang Liu, Li-cheng Jiao, Hong-wei Huo
Venue: Proceedings of the 2008 International Conference on BioMedical Engineering and Informatics - Volume 01 (2008)

For the motif discovery problem of DNA sequences, a greedy two-stage Gibbs sampling algorithm is presented, and the related software package is called Greedy MotifSAM. Based on position weight matrix (PWM) motif model, a greedy strategy for choosing the initial parameters of PWM is employed. Two sampling methods, site sampler and motif sampler, are used. Site sampler is used to find one occurrence per sequence of the motif in the dataset. Motif sampler is used to find zero or more non-overlapping occurrences of the motif in each sequence. The algorithm is capable of discovering several different motifs with differing numbers of occurrences in a single dataset. We use the binding sites (motif) information of eukaryotic transcription factors stored in TRANSFAC database to test our methods. The prediction accuracy, scalability and reliability are compared to several other methods.
Hierarchical Replication Techniques to Ensure Checkpoint Storage Reliability in Grid Environment
Authors: Fatiha Bouabache, Thomas Herault, Gilles Fedak, Franck Cappello
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

As High Performance platforms (Clusters, Grids, etc.) continue to grow in size, the average time between failures decreases to a critical level. An efficient and reliable fault tolerance protocol plays a key role in High Performance Computing. Rollback recovery is the most common fault tolerance technique used in High Performance Computing and especially in MPI applications. This technique relies on the reliability of the checkpoint storage. Most of the rollback recovery protocols assume that the checkpoint servers machines are reliable. However, in a grid environment any unit can fail at any moment, including components used to connect different administrative domains. Such failures lead to the loss of a whole set of machines, including the more reliable machines used to store the checkpoints in this administrative domain. Thus it is not safe to rely on the high MTBF (Mean Time Between Failures) of specific machines to store the checkpoint images. This paper introduces a new coordinated checkpoint protocol, which tolerates checkpoint server failures and clusters failures, and ensures a checkpoint storage reliability in a grid environment. To provide this reliability the protocol is based on a replication process. We propose new hierarchical replication strategies, with two different degrees of hierarchy, adapted to the topology of cluster of clusters. Our solution exploits the locality of checkpoint images in order to minimize inter-cluster communication.We evaluate the effectiveness of our two hierarchical replication strategies through simulations against several criteria such as topology and scalability.
EMMA: an automated intelligent actor in e-drama
Authors: Li Zhang, Marco Gillies, John Barnden
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2008)

We report work on adding an improvisational AI actor and 3D emotional animation to an existing edrama program, a system for dramatic improvisation in simple virtual scenarios. The improvisational AI actor has an affect-detection component, aimed at detecting affective aspects of human-controlled characters' textual input. It also makes an appropriate response to stimulate the improvisation based on this affective understanding. A distinctive feature of our work is a focus on the metaphorical ways in which affect is conveyed. Moreover, we have also introduced how the detected affective states activate the animation engine to produce emotional gestures for human-controlled characters. Finally, we report user testing conducted for the AI actor. Our work contributes to the conference themes on affective user interfaces, natural language processing and emotionally believable gesture generation.
A Conformal Mapping Approach for Shoe Last Design
Authors: Sikyung Kim, Mohammad Mynuddin Gani Mazumder, Se Jin Park
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

Customized shoe making is receiving increased interest from shoe manufacturers as a solution to alleviate the growing burdens associated with foot problems. Design of shoe ``lasts" is a central activity in customized shoe manufacture and is traditionally based on bare eyes and skilful hands. This results in errors in the design of lasts and, in recent years, the Free Form Deformation (FFD) was introduced that utilizes a restricted number of control points to transform the 3D foot data into 3D last data. However this scheme does not provide the design method for the major dimensions of the last. To overcome this problem a new method for last design was developed that takes the three dimensional foot data and carries out its analysis using LFFD and the Schwarz-Christoffel algorithm but which improves this further by means of a conformal mapping function in terms of accuracy over the conventional last design. Further research is needed to assess the practicalities and its industrial application in shoe manufacture. 1. Problem Description In modern times, people do not exercise enough, have become overweight and experience foot problems. As normal walking is not carried out, foot problems have become an important health issue. Customized shoe making has received increased interest of the shoe manufacturers to decrease the burdens associated with foot problems. Design of shoe "lasts" is a central activity in shoe manufacture but modification of the shape of the lasts is a complex process which involves many parameters: heel height; toe spring; girth length; stick length; etc. Traditionally, the last design method draws on bare eyes and skilful hands but these result in errors in the design of lasts. It is essential to analyze foot shape, 3D measureement of the foot and foot pressure analysis as the first step of customized shoe making includes all of these[1,2,3,4]. For 3D foot measurement, Mochimaru [5] proposed the FFD scheme to design the shoe last. However this scheme does not provide the design method for the major dimensions, such as ball-girth, heel circumference, ball-width and insole length. To solve this problem the Limb Line Free Form Deformation (LFFD) had been proposed but there were still some errors as the LFFD scheme is based on 3D interpolation that uses a restricted number of control points to transform the 3D foot data into 3D last data. 2. Research Questions The restriction of control points motivated our
A parallel approach for self-adjoint singular perturbation problems using Numerov's scheme
Authors: R. K. Bawa
Venue: International Journal of Computer Mathematics (2007)

In this paper, we considered singularly perturbed self-adjoint boundary-value problems and proposed a computational technique based on Numerov's scheme, which is also suitable for parallel computing. The whole domain is divided into three non-overlapping subdomains, and corresponding subproblems are obtained by using zeroth-order approximations of the solution at the boundaries of these subproblems. The subproblems corresponding to boundary-layer regions are solved using Numerov's method after the introduction of suitable stretching variables and the solution of the reduced problem is taken as an approximate solution in the outer region. A numerical example is provided to show the efficiency and accuracy of the technique.
RTMG: Scheduling real-time distributable threads in large-scale, unreliable networks with low message overhead
Authors: Kai Han, Binoy Ravindran, E. D. Jensen
Venue: Proceedings of the 13th International Conference on Parallel and Distributed Systems - Volume 01 (2007)

We consider scheduling real-time distributable threads in the presence of node/link failures, message losses, and dynamic node joins and departures. We present a distributed scheduling algorithm called RTMG. The algorithm uses gossip-based communication for discovering eligible nodes. Traditionally, gossip protocols incur high message overhead. We explain that this problem is not that serious. We present a hybrid message propagation protocol with lower message overhead, and improve it by evenly distributing the overhead into all gossip rounds. In scheduling local thread sections, RTMG exploits slacks to optimize gossip time utilization. Thereby, it satisfies end-to-end time constraints with probabilistic assurance. Our simulation studies verify our analytical results.
An accurate analytical crosstalk model for RC interconnect
Authors: P. Chandra Sekhar, Rameshwar Rao
Venue: Proceedings of the 2nd WSEAS International Conference on Circuits, Systems, Signal and Telecommunications (2008)

In recent times, crosstalk noise is playing a vital role in the performance of VLSI circuits, due to miniaturization of the feature size. In this paper, we propose an accurate, fast and simple closed form solution to estimate crosstalk noise between two adjacent wires, using RC interconnect model. The salient features of our proposed metric are minimization of computational overhead, elimination of adjustment to estimate the peak amplitude and pulse width of the noise waveform. Numerical calculations of our model are compared with SPICE simulation and other metrics by plotting the noise voltage verses time. It is evident from the experimental results that our crosstalk noise model in time domain is closely matched with SPICE simulation at a minimum estimation error of 0.62%.
Generation of two-dimensionally variable saturated hydraulic conductivity fields: Model theory, verification and computer program
Authors: Antti Taskinen, Hannu Sirviö, Michael Bruen
Venue: Computers Geosciences (2008)

The theory for the generation method of spatially variable K"s fields, using a set of scaling factors of log-normally distributed random field with two-dimensional correlation structure, is compiled from different sources. It is developed further by derivation of computational formulas of model parameters for a general case. The user of the method needs to define the mean, coefficient of variation and correlation length of the K"s fields. Both isotropic and anisotropic fields can be generated. The method and the computer program, which is provided for readers, are verified by analyzing example generations carried out by set of different parameter values. Since the materializations of the set values in generated fields were found satisfactorily accurate and their distributions cohered the model structure, the method and the computer program can be considered a useful and reliable tool for simulation of spatially variable hydraulic conductivity fields. However, the way of the method treating the covariance structure of the random vector limits the field size or the number of nodes where the K"s values are to be generated.
Covering two-edge-coloured complete graphs with two disjoint monochromatic cycles
Authors: Peter Allen
Venue: Combinatorics, Probability and Computing (2008)

In 1998 Łuczak Rödl and Szemerédi [7] proved, by means of the Regularity Lemma, that there exists n0 such that, for any n ≥ n0 and two-edge-colouring of Kn, there exists a pair of vertex-disjoint monochromatic cycles of opposite colours covering the vertices of Kn. In this paper we make use of an alternative method of finding useful structure in a graph, leading to a proof of the same result with a much smaller value of n0. The proof gives a polynomial-time algorithm for finding the two cycles.
On a numerical model for gasification of biomass materials
Authors: Mahdi Vaezi, Mohammad Passandideh-Fard, Mohammad Moghiman
Venue: Proceedings of the 1st WSEAS International Conference on Computational Chemistry (2007)

In this paper, a thermochemical equilibrium model is used to predict the performance of a downdraft gasifier. Numerical results are shown to be in good agreement with those of the experiments. Different biomass materials are tested using the model and forest residual is shown to be the most energetic one. For this material, the gasification temperature, syngas composition and calorific value are calculated. The effects of moisture content, air/fuel ratio, air inlet temperature and steam/fuel ratio are also investigated. The air inlet temperature is found to be the only way to increase the gas calorific value and cold gas efficiency. The steam/fuel ratio, on the other hand, plays a key rule in controlling the gasification temperature and H2/CO ratio.
An efficient preconditioning scheme for real-fluid mixtures using primitive pressure-temperature variables
Authors: Nan Zong, Vigor Yang
Venue: International Journal of Computational Fluid Dynamics (2007)

An improved preconditioning scheme incorporating a unified treatment of general fluid thermodynamics is developed for treating fluid flows over the entire regime of fluid thermodynamic states at all speeds. All of the thermodynamic and numerical properties (such as eigenvalues and Jacobian matrices) are derived directly from fundamental thermodynamics theories, rendering a self-consistent and robust algorithm. Further efficiency is obtained by employing temperature instead of enthalpy as the primary dependent variable in the preconditioned energy equation. No iterative solution of a real-fluid equation of state is required. This approach, combined with the use of explicit treatments of temporal and spatial derivatives, results in a scheme for which load balance is much easier to achieve in a distributed computing environment. A numerical stability analysis is performed to assess the effectiveness of the scheme at various fluid thermodynamic states. Sample calculations are also carried out. These include injection and mixing of cryogenic fluids and flame dynamics of coaxial jets of liquid oxygen and methane under supercritical conditions. The robustness and efficiency of the present work are demonstrated over a wide range of thermodynamic and flow conditions.