In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this paper, the author focuses on recommendation of a fresh method for retrieving image. For multi presentation of image in Convolutional Neural Network (CNN),

Objectives: This research aims to assess the suitability and availability of climatic conditions for olive cultivation in Iraq. The study identifies the most and least suitable areas, along with intermediate areas, utilizing the ArcMap program for mapping and delineating agriculturally favorable regions. Methods: A descriptive approach was employed in this research, as an analytical approach was deemed essential for describing and analyzing data to attain scientific accuracy. Results: The research findings indicate that certain areas, namely Mosul, Erbil, Sulaymaniyah, and Kirkuk, exhibit high suitability for olive tree cultivation. The station at Al-Rutba demonstrates moderate feasibility, while Basra, Nasiriyah, Amarah, Baghdad,

          In the present research, a crane frame has been investigated by using finite element method. The damage is simulated by reducing the stiffness of assumed elements with ratios (10% and 20 %) in mid- span of the vertical column in crane frame. The cracked beam with a one-edge and non-propagating crack has been used. Six cases of damage are modeled for crane frame and by introducing cracked elements at different locations with ratio of depth of crack to the height of the beam (a/h) 0.1, 0.20. A FEM program coded in Matlab 6.5 was used to model the numerical simulation of the damage scenarios. The results showed a decreasing in the five natural frequencies from undamaged beam which means

A survey of plant-parasitic nematode genera associated with roots of mature date palm trees was conducted in central Iraq to study their occurrence, population density, and geographical distribution. This study in Baghdad, Babil, Diyala, Karbela, Najaf, and Wasit governorates was conducted from 2019 to 2023, during the months from October to April. A total of 150 soil and root samples were gathered from 46 fields, and plant-parasitic nematodes were extracted and morphologically identified to genus level. Eleven genera of plant-parasitic nematodes were detected in the declining order of frequency: Tylenchorhynchus spp. (20%) in Baghdad, Babil, Diyala, Karbala, and Najaf; Meloidogyne spp. (17.3%) in Baghdad, Babil, Diyala, Najaf, and

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

Evolutionary algorithms are better than heuristic algorithms at finding protein complexes in protein-protein interaction networks (PPINs). Many of these algorithms depend on their standard frameworks, which are based on topology. Further, many of these algorithms have been exclusively examined on networks with only reliable interaction data. The main objective of this paper is to extend the design of the canonical and topological-based evolutionary algorithms suggested in the literature to cope with noisy PPINs. The design of the evolutionary algorithm is extended based on the functional domain of the proteins rather than on the topological domain of the PPIN. The gene ontology annotation in each molecular function, biological proce

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance