This study was for searching for Cholera Bacteria serotype which causes epidemiology Cholera in the 2007 in a fast method which contains (Rapid Visual Test) (Crystal V.C.) which was used for the first time in Iraq to diagnosis of Cholera Bacteria & compared with the traditional bacteriology method. The Cholera disease is one of the most dangerous epidemiological diseases which lead to death with a percentage of (50 – 70) % in the severe cases for untreated patients . For this purpose, 100 samples of stool from the patients from a (13) hospitals in Baghdad Governorate in the period from August to the end of December. The Cholera was diagnosis in two methods, 1st method was the fast method using the nitrocellulose which is coated with anti-

    Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th

Deep learning convolution neural network has been widely used to recognize or classify voice. Various techniques have been used together with convolution neural network to prepare voice data before the training process in developing the classification model. However, not all model can produce good classification accuracy as there are many types of voice or speech. Classification of Arabic alphabet pronunciation is a one of the types of voice and accurate pronunciation is required in the learning of the Qur’an reading. Thus, the technique to process the pronunciation and training of the processed data requires specific approach. To overcome this issue, a method based on padding and deep learning convolution neural network is proposed to

Importance of study :

The interesting of industrial sector and developing it after corner stone. It is important to build economic balanced and get behind and front linkage for transformative industrials, and this is important to get balanced.

The value of transformative industry sector is more important than other sectors in economy, and this is reflect the capital in industrial sector .Industry  sector is larger than other sectors ,so it regards the motive which moving the economic wheel .

The  problem :

The research treats reduction and retreat the ind

The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

The aim of this research is to study the influence of additives on the properties of soap greases, such as lithium, calcium, sodium, lithium-calcium grease, by adding varies additives, such as graphite, molybdenum disulfide, carbon black, corrosion inhibitor, and extreme pressure.
These additives have been added to grease to obtain the best percentages that improve the properties of grease such as load carrying, wear resistance, corrosion resistance, drop point, and penetration.
The results showed the best weight percentages to all types of grease which give good properties are 1.5% extreme pressure additive, 3% graphite, 1% molybdenum disulfide, 2.5% carbon black.
The other hand, the best weight percentage for corrosion inhibit