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Numerical reproducibility failures rise in parallel computation because of the non-associativity of floating-point summation. Optimizations on massively parallel systems dynamically modify the floating-point operation order. Hence, numerical results may change from one run to another. We propose to ensure reproducibility by extending as far as possible the IEEE-754 correct rounding property to larger...
In the present work, Particle swarm optimisation (PSO) based Tsallis entropy method is employed to segment the buried object SONAR images. This SONAR detects the objects present beneath the seabed in ocean. Objects may be pipelines, and unexploded ordinances buried beneath the seabed. Computer vision for object detection is required when SONAR is equipped in autonomous underwater vehicle. The vehicle...
While there has been many studies on the efficient design of p-cycles focusing on optimizing their spare capacity efficiency, few of them consider such a design under the wavelength continuity assumption, i.e., no wavelength converter at any node. Consequently, few authors look at the routing and wavelength assignment in the context of p-cycles, where p-cycles have to be assigned the same wavelength...
Log-likelihood ratios (LLRs) are efficient metrics used in the decoding of modern channel codes such as low-density parity-check and turbo codes. LLR calculation, however, can be a complex task since LLRs are usually complicated nonlinear functions of the channel output. In multi-input multioutput (MIMO) channels, the complexity of the calculation increases exponentially with the number of antennas...
Accurate cardinality estimates are essential for a successful query optimization. This is not only true for relational DBMSs but also for RDF stores. An RDF database consists of a set of triples and, hence, can be seen as a relational database with a single table with three attributes. This makes RDF rather special in that queries typically contain many self joins. We show that relational DBMSs are...
This article analyses the calculation problems concerning mean square error of side length, mean square error of starting point and triangle figure condition which will affect comprehensively error of intersection point, especially linear intersection minor angle triangle's intersection angle between 150° ~ 180° intersection point's error optimization and the optimum solution of point transfer coordinate...
We present a Nonlinear Model Predictive Control (NMPC) algorithm for real-time control of large-scale river networks in delta areas. The algorithm consists of an iterative, finite-horizon optimization of the system over a short-term control horizon. The underlying set of nonlinear internal process models represents relevant physical phenomena such as flow routing in the river network, and the dynamics...
The basic idea of the video data mining is based on the content of multimedia features and the semantics related to these properties, from large multimedia data sets and analysis of the underlying discovery, effective, valuable, and understandable patterns. In this paper, based on multi-encoding mode for real-time trans-coding of video streams we firstly research on the input data reuse pattern matching...
Multiple-input and multiple-output (MIMO) radar systems have garnered significant interest due to their ability to generate additional target radar returns. These additional returns have the potential to improve tracking performance in terms of target tracking accuracy and resource use. This effort examines radar pulse control for target tracking optimization in a MIMO radar architecture. Specifically,...
We propose an optimization-based framework to minimize the energy consumption in a sensor network when using an indoor localization system based on the combination of received signal strength (RSS) and pedestrian dead reckoning (PDR). The objective is to find the RSS localization frequency and the number of RSS measurements used at each localization round that jointly minimize the total consumed energy,...
The estimation of the mid-sagittal plane (MSP) is a known problem with several applications in neuroimage analysis. As advance to the state-of-the-art, we present a considerably better approach for MSP extraction based on bilateral symmetry maximization and a more suitable error metric to compare MSP estimation methods. The proposed method was quantitatively evaluated using three other state-of-the-art...
Symmetry and inverse consistency are two important features for deformable image registration in medical imaging analysis. This work presents a novel registration method computing symmetric and inverse-consistent image alignment efficiently while preserving high accuracy and consistency of the mapping. This is achieved by optimizing a symmetric energy functional estimating forward and backward transformations...
The Alcoholism is an addictive disorder, which causes social, physical, psychiatric and neurological damages on individuals. In this paper, Global Field Synchronization (GFS) measurements of multi channel ERP (Event Related Potential) signals in Delta, Theta, Alpha, Beta and Gamma frequency bands are used as discriminating feature vectors in the classification of alcoholic and non-alcoholic control...
The high-pressure sheet metal forming of tailor rolled blanks allows the production of optimized components specially developed for their future function, which cannot be made from conventionally rolled sheet metal. The research aims at showing that the two processes, i.e. flexible rolling and high-pressure sheet metal forming, can be well represented in finite element simulations. By linking the...
Design and optimization of microwave passive components is one of the most critical problems for RF IC designers. However, the state-of-the-art methods either have good efficiency but highly depend on the accuracy of the equivalent circuit models, which may fail the synthesis when the frequency is high; or fully depend on electromagnetic (EM) simulations, whose solution quality is high but are too...
To solve the problem of the static Bayesian network parameter learning using small sample, a study under restrained condition is proposed in the light of backward recursive accumulation parameter algorithm with priori constraints. Based on the variable of prior parameters, the constraints of domain knowledge described by uniform distribution and optimization algorithm, a Dirichlet distribution of...
In many real-world applications, the accurate number of clusters in the data set may be unknown in advance. In addition, clustering criteria are usually high dimensional, nonlinear and multi-model functions and most existing clustering algorithms are only able to achieve a clustering solution that locally optimizes them. Therefore, a single clustering criterion sometimes fails to identify all clusters...
With the never ending quest for high performance and cost/power efficient processor design in recent years, how to provide performance on adequate hardware and power budgets has become an important issue. In this paper, we review and evaluate several variable length history branch predictors for high performance processors and propose a modified branch predictor, f-TAGE, to improve critical path delay...
Each HIV-1 patient has a diverse population of virus strains in his/her body as the virus quickly replicates and mutates, requiring a combination drug therapy optimized to the patient's unique viral population. Towards this goal, prediction systems have been developed to deduce the susceptibility of a given HIV genotype to a single drug. Many are rule-based systems or rely on hand-crafted features...
In this paper, a communication strategy for the parallelized Artificial Bee Colony (ABC) optimization is proposed for solving numerical optimization problems. The artificial agents are split into several independent subpopulations based on the original structure of the ABC, and the proposed communication strategy provides the information flow for the agents to communicate in different subpopulations...
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