2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA

We present a new approach for face recognition system. The method is based on 2D face image features using subset of non-correlated and Orthogonal Gabor Filters instead of using the whole Gabor Filter Bank, then compressing the output feature vector using Linear Discriminant Analysis (LDA). The face image has been enhanced using multi stage image processing technique to normalize it and compensate for illumination variation. Experimental results show that the proposed system is effective for both dimension reduction and good recognition performance when compared to the complete Gabor filter bank. The system has been tested using CASIA, ORL and Cropped YaleB 2D face images Databases and achieved average recognition rate of 98.9 %

Combined sanger and ngs sequence analysis of the myostatin gene (mstn) in the Camelus dromedarius species

Different mutations have been identified in the myostatin gene (MSTN), some of which are responsible for protein inactivation and double muscling phenotype in mammals. So far, no extensive polymorphism survey has been carried out in Camelus dromedarius. We therefore performed a sequence analysis, adopting a combined strategy involving Sanger and next generation sequencing (NGS). Notably, 3.6 kb of the MSTN locus were Sanger sequenced in a population dataset including samples from Algeria (10), Tunisia (5), Egypt (9), Mauritania (5), Sudan (5) and Saudi Arabia (9). A further wholegenome dataset, including 7 C. dromedarius from Pakistan (1), Kenya (1), Saudi Arabia (3), Canary Islands (1) and Oman (1) were sequenced using the Illumina Hi-Seq 2000 technique at an average 15-fold coverage. Whole-genome NGS sequence data from 9 C. bactrianus and 7 C. ferus samples were also available for comparison. Overall, only four polymorphisms were detected, all of them were observed in intronic regions, corresponding to an average presence of one SNP per 1200 bps. Ten fixed sites were observed when comparing C. dromedarius MSTN sequences with those from C. bactrianus and C. ferus. The apparent low sequence diversity observed at the MSTN locus may reflect the peculiar evolutionary history of this species, with purifying selection and drift phenomena as the most likely acting forces.(Résumé d'auteur

A study of the gravitational wave form from pulsars II

We present analytical and numerical studies of the Fourier transform (FT) of the gravitational wave (GW) signal from a pulsar, taking into account the rotation and orbital motion of the Earth. We also briefly discuss the Zak-Gelfand Integral Transform. The Zak-Gelfand Integral Transform that arises in our analytic approach has also been useful for Schrodinger operators in periodic potentials in condensed matter physics (Bloch wave functions).Comment: 6 pages, Sparkler talk given at the Amaldi Conference on Gravitational waves, July 10th, 2001. Submitted to Classical and Quantum Gravit

The Zero-Removing Property and Lagrange-Type Interpolation Series

The classical Kramer sampling theorem, which provides a method for obtaining orthogonal sampling formulas, can be formulated in a more general nonorthogonal setting. In this setting, a challenging problem is to characterize the situations when the obtained nonorthogonal sampling formulas can be expressed as Lagrange-type interpolation series. In this article a necessary and sufficient condition is given in terms of the zero removing property. Roughly speaking, this property concerns the stability of the sampled functions on removing a finite number of their zeros

Integrating transposable elements in the 3D genome

Chromosome organisation is increasingly recognised as an essential component of genome regulation, cell fate and cell health. Within the realm of transposable elements (TEs) however, the spatial information of how genomes are folded is still only rarely integrated in experimental studies or accounted for in modelling. Whilst polymer physics is recognised as an important tool to understand the mechanisms of genome folding, in this commentary we discuss its potential applicability to aspects of TE biology. Based on recent works on the relationship between genome organisation and TE integration, we argue that existing polymer models may be extended to create a predictive framework for the study of TE integration patterns. We suggest that these models may offer orthogonal and generic insights into the integration profiles (or "topography") of TEs across organisms. In addition, we provide simple polymer physics arguments and preliminary molecular dynamics simulations of TEs inserting into heterogeneously flexible polymers. By considering this simple model, we show how polymer folding and local flexibility may generically affect TE integration patterns. The preliminary discussion reported in this commentary is aimed to lay the foundations for a large-scale analysis of TE integration dynamics and topography as a function of the three-dimensional host genome

Exact Traveling Wave Solutions of Nonlinear PDEs in Mathematical Physics Using the Modified Simple Equation Method

In this article, we apply the modified simple equation method to find the exact solutions with parameters of the (1+1)-dimensional nonlinear Burgers-Huxley equation, the (2+1) dimensional cubic nonlinear Klein-Gordon equation and the (2+1)-dimensional nonlinear Kadomtsev- Petviashvili-Benjamin-Bona-Mahony (KP-BBM) equation. The new exact solutions of these three equations are obtained. When these parameters are given special values, the solitary solutions are obtained

Melting and Solidification Study of As-Deposited and Recrystallized Bi Thin Films

Melting and solidification of as-deposited and recrystallized Bi crystallites, deposited on highly oriented 002-graphite at 423 K, were studied using reflection high-energy electron diffraction (RHEED). Films with mean thickness between 1.5 and 33 ML (monolayers) were studied. Ex situ atomic force microscopy was used to study the morphology and the size distribution of the formed nanocrystals. The as-deposited films grew in the form of three-dimensional crystallites with different shapes and sizes, while those recrystallized from the melt were formed in nearly similar shapes but different sizes. The change in the RHEED pattern with temperature was used to probe the melting and solidification of the crystallites. Melting started at temperatures below the bulk melting point of Bi, T0=544.5 K, and extended over a temperature range that depended on the size distribution of the crystallites. The as-deposited 1.5 ML film started to melt at T0-50 K and melted completely at T0-20 K. For films with higher coverage, the size distribution was observed to spread over a wider range with a larger mean value, resulting in a shift in the melting temperature range towards higher temperatures. Due to the shift in size distribution to higher values upon recrystallization, the recrystallized Bi crystallites showed a melting temperature range higher than that of the as-deposited crystallites. For the investigated conditions, all films were completely melted below or at T 0 of Bi. The characteristic film melting point, defined as the temperature at which the film melting rate with temperature is the fastest, showed a linear dependence on the reciprocal of the average crystallite radius, consistent with theoretical models. Of these models, the surface-phonon instability model best fits the obtained results. During solidification, the Bi films showed high amount of supercooling relative to T0 of Bi. The amount of liquid supercooling was found to decrease linearly with the reciprocal of the average crystallite size. © 2006 American Institute of Physics. [DOI: 10.1063/1.2208551

Condensation on (002) Graphite of Liquid Bismuth Far Below Its Bulk Melting Point

Condensation of thermally evaporated Bi on (002) graphite, at temperatures of 300-523K, was studied using in situ reflection high-energy electron diffraction (RHEED) and room temperature ex situ atomic force microscopy (AFM). For deposition at temperatures below 415±5K, transmission RHEED patterns of Bi appeared at an average thickness of ∼0.5 monolayer (ML). AFM images showed that the film consisted of crystallites in the shape of triangular step pyramids with step heights corresponding to single and double Bi layers in the [111] direction. This morphology indicates crystallization from the vapor. For deposition at higher temperatures, diffuse RHEED patterns appeared independent of the deposited thickness. When these films were cooled, clear transmission patterns of crystalline Bi appeared. After cooling to near room temperature, the melting and solidification behaviors of these films were investigated with RHEED. Upon subsequent heating, the topmost layers of the probed Bi crystallites started to lose long-range order at ∼10-15K below the Bi bulk melting point, T0=544.52K. When crystallized from the melt, supercooling by ∼125K below T0 was observed. These results indicate that Bi condensed on graphite in the form of supercooled liquid droplets when the graphite temperature was above 419K (T0-125). Below that temperature, Bi condensed in the solid phase. Bi films crystallized by cooling the liquid had crystal morphologies that depended on the degree of liquid supercooling. © 2005 The American Physical Society

Enhancing the performance of cancer text classification model based on cancer hallmarks

Deep learning (DL) algorithms achieved state-of-the-art performance in computer vision, speech recognition, and natural language processing (NLP). In this paper, we enhance the convolutional neural network (CNN) algorithm to classify cancer articles according to cancer hallmarks. The model implements a recent word embedding technique in the embedding layer. This technique uses the concept of distributed phrase representation and multi-word phrases embedding. The proposed model enhances the performance of the existing model used for biomedical text classification. The result of the proposed model overcomes the previous model by achieving an F-score equal to 83.87% using an unsupervised technique that trained on PubMed abstracts called PMC vectors (PMCVec) embedding. Also, we made another experiment on the same dataset using the recurrent neural network (RNN) algorithm with two different word embeddings Google news and PMCVec which achieving F-score equal to 74.9% and 76.26%, respectively