The present study introduces description of a new species of genus Arboridia Zakhvaticin 1946, based on a large collection of Cicadellids. External morphological characters particularly male genitalia were discussed and illustrated. The genus Arboridia Zalchvatkiia (Typhlocybinae: Erythroneurini) contains small slender, fragil and attractively coloured and patterned leafhoppers. It was erected by Zakhvatkin in 1946 (Zalchvatkin, 1946). The overall length of adults ranges from 2.5 to 3.4 mm. Members of this genus can be recognized by inner apical cell of forewing which is long with oblique base; Cu confluent with this base at a point near the middle of the length of inner apical cell; two prominent circular deep brown spots on vertex (Zal

We introduced the nomenclature of orthogonal G -m-derivations and orthogonal generalized G -m-derivations in semi-prime G -near-rings and provide a few essentials and enough provision for generalized G -n-derivations in semi-prime G -near-rings by orthogonal.

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

Background: The therapeutic goal of orthodontic treatment is to establish ideal occlusion which includes both static and functional aspects. The objective of this study was to clarify functional occlusal treatment goals by analyzing functional occlusion in subjects with established normal occlusion and identify the differences between canine protected occlusion and group function occlusion. Materials and Methods: The sample consisted of 62 subjects with normal occlusion and with an age range of (18-25 years).Functional occlusal contacts during lateral excursion were identified on a fully adjustable articulator, and then the samples were classified according to: 1) Type of functional occlusion: A) Canine protected occlusion group (canine pr

Background: Although the new treatment methods developed in recent years are aiming to minimize the need for cooperation of the patients; however, the latter still important factor the treatment. The aim of the study was to evaluate the cooperation level of Class III maloc-clusion patients with orthodontic treatment. Materials and methods: This study followed a cross-sectional style; the targeted population was patients with Class III malocclusion who were treated with three different types of orthopaedic appliances. Four questionnaires were delivered to the patient, patient’s parents, and orthodontists. Statistical analyses of the study were performed with SPSS 20.0 software. Descriptive analyses were presented using fre-quency, percenta

Objectives: The study aims to assess the school refusal behavior of first class pupils at primary schools and identifying the relationship between the school refusal behavior and some of socio-demographic characteristics for the pupils.

Methodology:  A descriptive-analytic study was initiated from November 1^st, 2012 to April 1^st, 2013. A random sample of 411 students is selected from a probability stratified sample of 17 primary schools for both sexes in 4 sectors in Baghdad Al-Rasafa and Al-Karkh districts which are selected randomly from first class of primary school. A Self administrative questionnaire (Parents' Version) which constructed by the rese

The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet