In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

The Early – Middle Miocene Ghar and Lower Fars sedimentary succession at the representative oil-well Nu-18 of the Nahr Umr oil field south Iraq; is taken by this study to investigate the sedimentological to reservoir rock facies buildups and related reservoir zonation; as first rock-typing attempt for the both formations. The sedimentological characterization of the Early Miocene Ghar formation is mainly comprised by successive buildups of sands-gravels and sandstones, whereas; the Middle Miocene Lower Fars formation is started by limestone, limestone-marly/marl anhydritic, upgraded into interbedded-series of marl and anhydrite facies, with less-common occurrences of thin-sandstone interlayers, terminated by marl-sandy-secti

Birds of prey (Raptors) are top predator avian species that many migrate annually through Mesopotamian marshes in southern Iraq toward their wintering grounds in Arabia and Africa, while others are breeding residents; however, information on their current status is scarce. From January 2016 to April 2019, a total of 20 field expeditions were conducted in the geographical zone of the Mesopotamian marshes, wetlands of international importance. The survey covered the Central Marshes, Al-Hammar and Hawizeh Marsh. One of the objectives of the field surveys is to list the raptors species that wintering and/or migrating through the Mesopotamian marshes and to understand their current spatial and temporal distribution. In the present study, a to

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

Gender classification is a critical task in computer vision. This task holds substantial importance in various domains, including surveillance, marketing, and human-computer interaction. In this work, the face gender classification model proposed consists of three main phases: the first phase involves applying the Viola-Jones algorithm to detect facial images, which includes four steps: 1) Haar-like features, 2) Integral Image, 3) Adaboost Learning, and 4) Cascade Classifier. In the second phase, four pre-processing operations are employed, namely cropping, resizing, converting the image from(RGB) Color Space to (LAB) color space, and enhancing the images using (HE, CLAHE). The final phase involves utilizing Transfer lea

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

Peer-Reviewed Journal

The current study is a taxonomic account of three gastrotrich species that belong to Chaetonotidae (Phylum Gastrotricha) namely Ichthydium auritum Brunson, 1950 Lepidodermella squamata (Dujardin, 1841) and Chaetonotus anomalus Brunson, 1950. These species are registered as a new record from Iraq and were collected from several locations along the main outfall drain (MOD) in south of Baghdad, from January to December 2020. The species described in this article were found to be related to Hydrilla and Ceratophyllum and prefer environments rich in detritus and decomposing organic matter. The worms preferred water that is salty, hard, alkaline, and had good oxygen content.

This study included a survey and review of the scientific names of the marsh insects (aquatic and surrounding it) for the purpose of unifying and updating the database.
The survey reveals 109 species under 77 genera that belong to 32 families and 7 orders as follow: Coleoptera (44 species), Diptera (7 species) Ephemeroptera (2 species), Hemiptera (14 species), Hymenoptera (11 species), Lepidoptera (2 species) and Odonata with 29 species.
Information of specimens' collection for each species, synonyms and geographical distribution were provided.