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To facilitate comparisons of electromagnetics solvers in terms of accuracy, efficiency, parallel scaling, and other relevant parameters, several benchmarking problems and their accurate solutions are provided. Solutions of some of the world's largest scattering problems involving conducting and dielectric spheres, NASA almond, and other useful real-life geometries are provided. An interactive on-line...
The recognition of forged fingerprints at crime scenes is a very old challenge. Various forgery techniques can be applied to produce such traces. However, the detection of such forgeries usually involves a thorough manual inspection. For the example of fingerprints printed using ink-jet printers and artificial sweat, first pattern recognition approaches are proposed in prior work employing two different...
In this paper we present an innovative method for counting people from zenithal mounted cameras. The proposed method is designed to be computationally efficient and able to provide accurate counting under different realistic conditions. The method can operate with traditional surveillance cameras or with depth imaging sensors. The validation has been carried out on a significant dataset of images...
Today's infrastructure clouds provide resource elasticity (i.e. Auto-scaling) mechanisms enabling self-adaptive resource provisioning to reflect variations in the load intensity over time. These mechanisms impact on the application performance, however, their effect in specific situations is hard to quantify and compare. To evaluate the quality of elasticity mechanisms provided by different platforms...
The proliferation of RF-based indoor localization solutions raises the need for testing systems that enable objective evaluation of their functional and non functional properties. We introduce a testbed and cloud infrastructure for supporting automatized benchmarking of RF-based indoor localization solutions under controlled interference. For evaluating the impact of RF interference on the performance...
This work proposes a practical technique to reduce the evaluation cost of multi-core based systems, when these systems are evaluated with parallel benchmarks. The proposed technique highlights the amount of redundancy in aset of parallel benchmarks and reduces this set to a subset of benchmarks such that: (i) the selected benchmarks are representative or non-redundant - i.e., the series of performance...
Texture recognition is an important aspect of many computer vision applications. Local binary pattern (LBP) based texture algorithms have gained significant popularity in recent years and have been shown to be useful for a variety of tasks. While over the years a variety of LBP algorithms have been introduced in the literature, what is missing is a comprehensive evaluation of their performance. In...
Adaptive performance management solutions often rely on models that require accurate resource demand measures that are estimated in an on-line manner. However it is typically not possible to directly measure resource demands at the abstraction they are needed, e.g., for a software service within an application server that is invoked by a URL. For such cases, linear regression techniques are often...
The great success and high number of participants in pattern recognition related competitions last years show an important improvement of recognition and classification approaches. This success is unconceivable without the availability of huge datasets of real world data. We have invited for proposals for competitions to be held in the framework of the 12th International Conference on Frontiers in...
Understanding input/output (I/O) performance in high performance computing (HPC) is becoming increasingly important as the gap between the performance of computation and I/O widens. In this paper we propose a methodology to predict an application's disk I/O time while running on High Performance Computing Modernization Program (HPCMP) systems. Our methodology consists of the following steps: 1) Characterize...
Protein fold recognition task is important for understanding the biological functions of proteins. The adaptive local hyperplane (ALH) algorithm has been shown to perform better than many other renown classifiers including support vector machines, K-nearest neighbor, linear discriminant analysis, K-local hyperplane distance nearest neighbor algorithms and decision trees on a variety of data sets....
The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Mission has been recommended in the National Research Council Earth Science Decadal Survey as a key component of the future climate observing system. NASA and NOAA share responsibility for CLARREO. The NOAA component involves the continuity of measurements of incident solar irradiance and Earth energy budget by flying the Total Solar...
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