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),

The search involve the synthesis of some new 1,3-oxazepine and 1,3-diazepine derivatives were synthesized from Schiff base. The Schiff base (VIII) prepared from reaction of aldehyde (IV) derived from L-ascorbic acid with aromatic amine ([2-(4- nitrophenyl)-5-(4-aminophenyl)-1,3,4-oxadiazole] (VII). Oxazepine compounds (IX-XI) were synthesized from the cyclic condensation of Schiff base (VIII) with (maleic, phthalic and 3-nitrophthalic) anhydride, compounds (IX-XI) that were reacted with p-methoxyaniline to give diazepine derivatives (XII-XIV). The structures of the new synthesized compounds have been confirmed by physical properties and spectroscopy measurements such as FTIR, and some of them by 1 H-NMR, 13 CNMR, Mass, and evaluated

Unconfined compressive strength (UCS) of rock is the most critical geomechanical property widely used as input parameters for designing fractures, analyzing wellbore stability, drilling programming and carrying out various petroleum engineering projects. The USC regulates rock deformation by measuring its strength and load-bearing capacity. The determination of UCS in the laboratory is a time-consuming and costly process. The current study aims to develop empirical equations to predict UCS using regression analysis by JMP software for the Khasib Formation in the Buzurgan oil fields, in southeastern Iraq using well-log data. The proposed equation accuracy was tested using the coefficient of determination (R²), the average absolute

      Cloud computing has gained considerable attention in academia and industry in recent years. The cloud facilitates data sharing and enables cost efficiency, thus playing a vital role today as well as for the foreseeable future. In this paper, a brief discussion the application of multi-tenant and load-balancing technologies to cloud-based digital resource sharing suitable for academic and digital libraries is presented. As a new paradigm for digital resource sharing, a proposal of improving the current user service model with private cloud storage for other sectors, including the medical and financial fields is offered. This paper gives a summary of cloud computing and its possible applications, combined with digital data optim

This paper proposed a new  method to study functional non-parametric regression data analysis with conditional expectation in the case that the covariates  are functional and the Principal Component Analysis was utilized to de-correlate the multivariate response variables. It  utilized the formula of the Nadaraya Watson estimator (K-Nearest Neighbour (KNN)) for prediction with different types of the semi-metrics, (which are based on Second Derivative and Functional Principal Component Analysis (FPCA))  for measureing the closeness between curves.  Root Mean Square Errors is used for the  implementation of this model which is then compared to the independent response method. R program is used for analysing data. Then, when  the cov

Evaluation study was conducted for seismic interpretation using two-dimensional seismic data for Subba oil field, which is located in the southern Iraq. The Subba oil field was discovered in 1973 through the results of the seismic surveys and the digging of the first exploratory well SU-1 in 1975 to the south of the Subba oil field. The entire length of the field is 35 km and its width is about 10 km. The Subba oil field contains 15 wells most of them distributed in the central of the field.

     This study is dealing with the field data and how to process it for the purpose of interpretation; the processes included conversion of field data format, compensation of lost data and noise disposal, as well as the a

Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

     Machine learning-based techniques are used widely for the classification of images into various categories. The advancement of Convolutional Neural Network (CNN) affects the field of computer vision on a large scale. It has been applied to classify and localize objects in images. Among the fields of applications of CNN, it has been applied to understand huge unstructured astronomical data being collected every second. Galaxies have diverse and complex shapes and their morphology carries fundamental information about the whole universe. Studying these galaxies has been a tremendous task for the researchers around the world. Researchers have already applied some basic CNN models to predict the morphological classes

       The climate changes had been recognized as one of the major factors responsible for land degradation, which has a significant impact on diverse aspects. The present study aims to estimate how the climate change can influence land degradation in the south areas of Baghdad province (Al-Rasheed, Al-Mahmudiyah, Al-Yusufiyah, Al-Madaen, and Al-Latifiyah). The Satellite Landsat-8 OLI and satellite Landsat-5 TM sensor imagery were used to extent land degradation for the period (2010-2019). ArcGIS V.10.4 was applied to manage and analysis the satellite image dataset, including the use of climate factors data from the European Center for Climate Forecasts (ECMWF) by reanalyzes and extraction datasets. To achieve work objectives, many

The Digital Elevation Model (DEM) has been known as a quantitative description of the surface of the Earth, which provides essential information about the terrain. DEMs are significant information sources for a number of practical applications that need surface elevation data. The open-source DEM datasets, such as the Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER), the Shuttle Radar Topography Mission (SRTM), and the Advanced Land Observing Satellite (ALOS) usually have approximately low accuracy and coarser resolution. The errors in many datasets of DEMs have already been generally examined for their importance, where their quality could be affected within different aspects, including the types of sensors, algor