The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

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

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

Background: A review of articles of method in treating compound phalangeal fractures by using mini-external fixator, elaborating the anatomy, mechanics, modalities of treatment, and complications of these types of fractures. Also, it compares between different studies regarding the functional results and final outcome. External fixation of phalangeal fractures is a good method for osteo synthesis in certain situations. The simplicity of the surgical procedure and the minimal disruption of the normal bone architecture also make it appealing. Objectives: Evaluating the functional results of the use of mini-external fixator for the treatment of compound fractures of phalangeal bones of the hand. Method: Our study consists of 15 patients, 12 we

Background: A review of articles of method in treating compound phalangeal fractures by using mini-external fixator, elaborating the anatomy, mechanics, modalities of treatment, and complications of these types of fractures. Also, it compares between different studies regarding the functional results and final outcome. External fixation of phalangeal fractures is a good method for osteo synthesis in certain situations. The simplicity of the surgical procedure and the minimal disruption of the normal bone architecture also make it appealing.Objectives: Evaluating the functional results of the use of mini-external fixator for the treatment of compound fractures of phalangeal bones of the hand.Method: Our study consists of 15 patients, 12 w

Automatic speaker recognition may achieve remarkable performance in matched training and test conditions. Conversely, results drop significantly in incompatible noisy conditions. Furthermore, feature extraction significantly affects performance. Mel-frequency cepstral coefficients MFCCs are most commonly used in this field of study. The literature has reported that the conditions for training and testing are highly correlated. Taken together, these facts support strong recommendations for using MFCC features in similar environmental conditions (train/test) for speaker recognition. However, with noise and reverberation present, MFCC performance is not reliable. To address this, we propose a new feature 'entrocy' for accurate and robu

Cloud point extraction is a simple, safe, and environmentally friendly technique for preparing many different kinds of samples. In this review, we discussed the CPE method and how to apply it to our environmental sample data. We also spoke about the benefits, problems, and likely developments in CPE. This process received a great deal of attention during preconcentration and extraction. It was used as a disconnection and follow-up improvement system before the natural mixtures (nutrients, polybrominated biphenyl ethers, pesticides, polycyclic sweet-smelling hydrocarbons, polychlorinated compounds, and fragrant amines) and inorganic mixtures were examined and many metals like (silver, lead, cadmium, mercury, and so on). We also find

The present study examines the extraction of lead (Pb), cadmium (Cd) and nickel (Ni) from   a contaminated soil by washing process. Ethylenediaminetetraacetic acid disodium salt (Na₂EDTA) and hydrochloric acid (HCl) solution were used as extractants.  Soil washing is one of the most suitable in-situ/ ex-situ remediation method in removing heavy metals. Soil was artificially contaminated with 500 mg/kg (Pb , Cd and Ni ).  A set of batch experiments were carried out at different conditions of  extractant concentration , contact time, pH and agitation speed. The results  showed  that the  maximum removal efficiencies  of (Cd, Pb  and Ni ) were (97, 88 and 24 )&nbs

Cloud point extraction is a simple, safe, and environmentally friendly technique for preparing many different kinds of samples. In this review, we discussed the CPE method and how to apply it to our environmental sample data. We also spoke about the benefits, problems, and likely developments in CPE. This process received a great deal of attention during preconcentration and extraction. It was used as a disconnection and follow-up improvement system before the natural mixtures (nutrients, polybrominated biphenyl ethers, pesticides, polycyclic sweet-smelling hydrocarbons, polychlorinated compounds, and fragrant amines) and inorganic mixtures were examined and many metals like (silver, lead, cadmium, mercury, and so on). We also find