Automatic eduction and statistical analysis of coherent structures in the wall region of a confine plane

This paper describes a vortex detection algorithm used to expose and statistically characterize the coherent flow patterns observable in the velocity vector fields measured by Particle Image Velocimetry (PIV) in the impingement region of air curtains. The philosophy and the architecture of this algorithm are presented. Its strengths and weaknesses are discussed. The results of a parametrical analysis performed to assess the variability of the response of our algorithm to the 3 user-specified parameters in our eduction scheme are reviewed. The technique is illustrated in the case of a plane turbulent impinging twin-jet with an opening ratio of 10. The corresponding jet Reynolds number, based on the initial mean flow velocity U0 and the jet width e, is 14000. The results of a statistical analysis of the size, shape, spatial distribution and energetic content of the coherent eddy structures detected in the impingement region of this test flow are provided. Although many questions remain open, new insights into the way these structures might form, organize and evolve are given. Relevant results provide an original picture of the plane turbulent impinging jet

Consensus image method for unknown noise removal

Noise removal has been, and it is nowadays, an important task in computer vision. Usually, it is a previous task preceding other tasks, as segmentation or reconstruction. However, for most existing denoising algorithms the noise model has to be known in advance. In this paper, we introduce a new approach based on consensus to deal with unknown noise models. To do this, different filtered images are obtained, then combined using multifuzzy sets and averaging aggregation functions. The final decision is made by using a penalty function to deliver the compromised image. Results show that this approach is consistent and provides a good compromise between filters.This work is supported by the European Commission under Contract No. 238819 (MIBISOC Marie Curie ITN). H. Bustince was supported by Project TIN 2010-15055 of the Spanish Ministry of Science

Kajian motivasi ekstrinsik di antara Pelajar Lepasan Sijil dan Diploma Politeknik Jabatan Kejuruteraan Awam KUiTTHO

Kajian ini dijalankan untuk menyelidiki pengaruh dorongan keluarga, cara pengajaran pensyarah, pengaruh rakan sebaya dan kemudahan infrastruktur terhadap motivasi ekstrinsik bagi pelajar tahun tiga dan tahun empat lepasan sijil dan diploma politeknik Jabatan Kejuruteraan Awain Kolej Universiti Teknologi Tun Hussein Onn. Sampel kajian ini beijumlah 87 orang bagi pelajar lepasan sijil politeknik dan 38 orang bagi lepasan diploma politeknik. Data kajian telah diperolehi melalui borang soal selidik dan telah dianalisis menggunakan perisian SPSS (Statical Package For Sciences). Hasil kajian telah dipersembahkan dalam bentuk jadual dan histohgrapi. Analisis kajian mendapati bahawa kedua-dua kumpulan setuju bahawa faktor-faktor di atas memberi kesan kepada motivasi ekstrinsik mereka. Dengan kata lain faktpr-faktor tersebut penting dalam membentuk pelajar mencapai kecemerlangan akademik

A Center-Median Filtering Method for Detection of Temporal Variation in Coronal Images

Events in the solar corona are often widely separated in their timescales, which can allow them to be identified when they would otherwise be confused with emission from other sources in the corona. Methods for cleanly separating such events based on their timescales are thus desirable for research in the field. This paper develops a technique for identifying time-varying signals in solar coronal image sequences which is based on a per-pixel running median filter and an understanding of photon-counting statistics. Example applications to 'EIT Waves' and small-scale dynamics are shown, both using data from the 193 Angstrom channel on AIA. The technique is found to discriminate EIT Waves more cleanly than the running and base difference techniques most commonly used. It is also demonstrated that there is more signal in the data than is commonly appreciated, finding that the waves can be traced to the edge of the AIA field of view when the data are rebinned to increase the signal-to-noise ratio.Comment: 15 pages, 7 Figures, Accepted to Journal of Space Weather and Space Climate; version 2 has slight text changes and updated movie URL