Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Elastic magnetic M1 electron scattering form factor has been calculated for the ground state J,T=1/2-,1/2 of 13C. The single-particle model is used with harmonic oscillator wave function. The core-polarization effects are calculated in the first-order perturbation theory including excitations up to 5ħω, using the modified surface delta interaction (MSDI) as a residual interaction. No parameters are introduced in this work. The data are reasonably explained up to q~2.5fm-1 .

beef and chicken meat were used to get Sarcoplasim, the chicken Sarcoplasim were used to prepare antibody for it after injected in rabbit, the antiserums activity were 1/32 by determined with Immune double diffusion test, the self test refer to abele for some antiserums to detected with beef sarcoplasim, which it mean found same proteins be between beef and chicken meat, which it refer to difficult depended on this immune method to detect for cheat of chicken meat with beef, so the antibody for beef sarcoplasim were removed from serum by immune absorption step to produce specific serum against chicken sarcoplasim that it used in Immune double diffusion test to qualitative detect for cheat beef with 5% chicken meat or more at least, and the

   A comparison of double informative and non- informative priors assumed for the parameter of Rayleigh distribution is considered. Three different sets of double priors are included, for a single unknown parameter of Rayleigh distribution. We have assumed three double priors: the square root inverted gamma (SRIG) - the natural conjugate family of priors distribution, the square root inverted gamma – the non-informative distribution, and the natural conjugate family of priors - the non-informative distribution as double priors .The data is generating form three cases from Rayleigh distribution for different samples sizes (small, medium, and large). And Bayes estimators for the parameter is derived under a squared erro

Abstract

 Metal cutting processes still represent the largest class of manufacturing operations. Turning is the most commonly employed material removal process. This research focuses on analysis of the thermal field of the oblique machining process. Finite element method (FEM) software DEFORM 3D V10.2 was used together with experimental work carried out using infrared image equipment, which include both hardware and software simulations. The thermal experiments are conducted with AA6063-T6, using different tool obliquity, cutting speeds and feed rates. The results show that the temperature relatively decreased when tool obliquity increases at different cutting speeds and feed rates, also it

Objective(s): To determine the impact of Chemotherapy upon the quality of life for patients with chronic myeloid
leukemia in Baghdad city.

Methodology: A descriptive study design was carried out The study was initiated from 30 January 2011 to October
2011.A purposive (non–probability) sample consisted of (130) patients with a chronic myeloid leukemia ,Who
attended to Baghdad Teaching Hospital and National Center for Research and Treatment of Hematology. The
sample criteria was the patients who were 18 years old and above, excluding the patients who suffered from
psychological problems and other chronic illnesses .A questionnaire was adopted and developed from European
Organization Research and treatment of Can

In this research, the effect of reinforcing epoxy resin composites with a filler derived from chopped agriculture waste from oil palm (OP). Epoxy/OP composites were formed by dispersing (1, 3, 5, and 10 wt%) OP filler using a high-speed mechanical stirrer utilizing a hand lay-up method. The effect of adding zinc oxide (ZnO) nanoparticles, with an average size of 10-30 nm, with different wt% (1,2,3, and 5wt%) to the epoxy/oil palm composite,  on the behavior of an epoxy/oil palm composite was studied with different ratios (1,2,3, and 5wt%) and an average size of  10-30 nm.  Fourier Transform Infrared (FTIR) spectrometry and mechanical properties (tensile, impact, hardness, and wear rate) were used to examine the composites. The FTIR

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei