Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes

This study was designed to test the effect of the treatment with aqueous extract of carrot seeds( Daucus carota) on fertility of male albino mice by effected on Body weight , testis weight ,secondary sex organs (prostate , seminal vesicle) and sperms properties .This experiment used (24) albino male mice aged(8-10)weeks. these animals were randomly divided into three groups contain two doses (200,400mgkg) were used from both extracts ,they were daily and orally given for (35)days ,and control group was given physiological saline. After the end of the experiment the animals were sacrificed after taken their body weights. The results were show: 1. A significant (p<0.05) increase in body weight and reproductive organs. 2

Acute lymphoblastic leukemia (ALL) is a cancer of the blood and bone marrow (spongy tissue in the center of bone). In ALL, too many bone marrow stem cells develop into a type of white blood cell called lymphocytes. These abnormal lymphocytes are not able to fight infection very well. The aim of this study was to investigate possible links between E3 SUMO-Protein Ligase NSE2 [NSMCE2] and increase DNA damage in the childhood patients with Acute lymphoblastic leukemia (ALL). Laboratory investigations including hemoglobin(Hb) ,white blood cell (WBC) , serum total protein , albumin ,globulin , in addition to serum total antioxidant activity (TAA) , Advanced oxidation protein products(AOPP) and E3 SUMO-Protein Ligase NSE2[NSMCE2]. Blood samples

The article is devoted to the issue of word-formation motivation, which does not lose its relevance and plays a role not only in disclosing formal-semantic relations between words of one language and has not only theoretical, but also applied significance. The authors consider word-formation motivation consistently in its varieties in a comparative way on the materials of so different languages as Russian and Arabic and approach the mechanism of achieving semantic equivalence of translation. To the greatest extent, word-formation activity today, due to objective reasons, affects some special branch (technical, medical, etc.) vocabulary, which is increasing from year to year in national dictionaries. This extensive material, selected

Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

In this work, satellite images for Razaza Lake and the surrounding area
district in Karbala province are classified for years 1990,1999 and
2014 using two software programming (MATLAB 7.12 and ERDAS
imagine 2014). Proposed unsupervised and supervised method of
classification using MATLAB software have been used; these are
mean value and Singular Value Decomposition respectively. While
unsupervised (K-Means) and supervised (Maximum likelihood
Classifier) method are utilized using ERDAS imagine, in order to get
most accurate results and then compare these results of each method
and calculate the changes that taken place in years 1999 and 2014;
comparing with 1990. The results from classification indicated that

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as computer vision, this study proposes a deep learning approach that utilizes a deep learning algorithm.

Nowadays, people's expression on the Internet is no longer limited to text, especially with the rise of the short video boom, leading to the emergence of a large number of modal data such as text, pictures, audio, and video. Compared to single mode data ,the multi-modal data always contains massive information. The mining process of multi-modal information can help computers to better understand human emotional characteristics. However, because the multi-modal data show obvious dynamic time series features, it is necessary to solve the dynamic correlation problem within a single mode and between different modes in the same application scene during the fusion process. To solve this problem, in this paper, a feature extraction framework of

A new Schiffbase derivative ligands [H4L1] and [H2L2] have been produced by condensed ophathaldehyde with ethylene diamine and [N1, N1'E, N1, N1'E)-N1, N1'-(1, 2-phenylenebis (methan-1-yl- 1ylidene)) diethane-1, 2-diamine] with 2-benzoyl benzoic acid. Schiffbase ligands have been separated and categorized by 1H, 13 C-NMR, (CHN) elemental analysis, UV-visible, mass spectroscopy and FTIR methods. Ten new coordination complexes were prepared and structurally diagnosed: [M(L1)Cl2] and [M2(L2)Cl2] where M(II) = Mn (II), Co(II), Ni(II), Cu(II) and Hg(II). The complexes have been typified by FTIR, UV-visble atomic absorption, molar conductance elemental analysis, and magnetic susceptibility. The details of the ligand (H4L1) compounds are getting a