In the image processing’s field and computer vision it’s important to represent the image by its information. Image information comes from the image’s features that extracted from it using feature detection/extraction techniques and features description. Features in computer vision define informative data. For human eye its perfect to extract information from raw image, but computer cannot recognize image information. This is why various feature extraction techniques have been presented and progressed rapidly. This paper presents a general overview of the feature extraction categories for image.

To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

The aim of the research is to use the data content analysis technique (DEA) in evaluating the efficiency of the performance of the eight branches of the General Tax Authority, located in Baghdad, represented by Karrada, Karkh parties, Karkh Center, Dora, Bayaa, Kadhimiya, New Baghdad, Rusafa according to the determination of the inputs represented by the number of non-accountable taxpayers and according to the categories professions and commercial business, deduction, transfer of property ownership, real estate and tenders, In addition to determining the outputs according to the checklist that contains nine dimensions to assess the efficiency of the performance of the investigated branches by investing their available resources T

Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and without memory (memory-less). The absence of memory in some metaheuristics will lead to the loss of the information gained in previous iterations. The metaheuristics tend to divert from promising areas of solutions search spaces which will lead to non-optimal solutions. This paper aims to review memory usage and its effect on the performance of the main SI-based metaheuristics. Investigation has been performed on SI metaheuristics, memory usage and memory-less metaheuristics, memory char

This research is to take advantage of the performance capabilities which the piano has become famous with and transfer the impact of that advantage to the possibilities of playing the violin. The research aims to introduce the effect of using the piano on the development of the violinists' musical potential. The research, in its literature, focuses on the interpretation of the impact on the possibility of both instruments (piano and violin) in two main sections: the piano (its origin, potential and role in music) and the violin (its origin, potential and role in music). The procedures of the research consisted of presenting a special analysis of a questionnaire consisting of a number of questions presented by the researcher to her resear

Background: Pleomorphic adenoma of the minor salivary gland is a rare benign tumor. It commonly occurs in the hard and soft palates. Treatment by surgical excision achieved success in improving the patient’s health. Objective: To evaluate the recurrence rate after surgical treatment of pleomorphic adenoma in minor salivary glands. Methods: This retrospective study included patients who attended the Maxillofacial Surgery Unit in Ghazi Al-Hariri Hospital, Baghdad, from 2019 to 2021, complaining of soft tissue lumps involving the soft and hard palate, buccal mucosa, and upper lip. After the provisional diagnosis of these lesions, a total surgical excision of the tumor with a safe margin of 1 mm was performed, and the biopsy was sent

Background: Pleomorphic adenoma of the minor salivary gland is a rare benign tumor. It commonly occurs in the hard and soft palates. Treatment by surgical excision achieved success in improving the patient’s health. Objective: To evaluate the recurrence rate after surgical treatment of pleomorphic adenoma in minor salivary glands. Methods: This retrospective study included patients who attended the Maxillofacial Surgery Unit in Ghazi Al-Hariri Hospital, Baghdad, from 2019 to 2021, complaining of soft tissue lumps involving the soft and hard palate, buccal mucosa, and upper lip. After the provisional diagnosis of these lesions, a total surgical excision of the tumor with a safe margin of 1 mm was performed, and the biopsy was sent for hist

Background: Color stability of glass ionomers (GIs) could be affected by many factors such as pH and consumption of liquid medications like antibiotics. Most common antibiotics used during childhood are amoxicillin suspension (AM.S) and azithromycin suspension (AZ.S) which have acidic and basic pH respectively. Aim: to evaluate and compare the effect of AM.S and AZ.S on color stability of nano resin-modified GI. Methods: Thirty disc of nano resin-modified glass ionomer (2mm height x 4mm diameter) were divided into three groups (n=10 for each) and independently exposed to AM.S, AZ.S, and artificial saliva (A.S.). Color stability was evaluated in triplicate by VITA Easyshade® before and after three immersion protocols, repeated over a thr

Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.

In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.