The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

The aim of this paper was to investigate the removal efficiencies of Zn⁺² ions from wastewater by adsorption (using tobacco leaves) and forward osmosis (using cellulose triacetate (CTA) membrane). Various experimental parameters were investigated in adsorption experiment such as: effect of pH (3 - 7), contact time (0  - 220) min, solute concentration (10 - 100) mg/l, and adsorbent dose (0.2 - 5)g. Whereas for forward osmosis the operating parameters studied were: draw solution concentration (10 - 150) g/l, pH of feed solution (4 - 7), feed solution concentration (10 - 100) mg/l. The result showed that the removal efficiency by using adsorption was 70% and the removal efficiency by using forward osmosis was 96.2 %. 

For criminal investigations, fingerprints remain the most reliable form of personal identification despite developments in other fields like DNA profiling. The objective of this work is to compare the performance of both commercial charcoal and activated carbon powder derived from the Alhagi plant to reveal latent fingerprints from different non-porous surfaces (cardboard, plain glass, aluminum foil sheet, China Dish, Plastic, and Switch). The effect of three variables on activated carbon production was investigated. These variables were the impregnation ratio (the weight ratio of KOH: dried raw material), the activation temperature, and the activation time. The effect factors were investigated using Central Composite Design

For criminal investigations, fingerprints remain the most reliable form of personal identification despite developments in other fields like DNA profiling. The objective of this work is to compare the performance of both commercial charcoal and activated carbon powder derived from the Alhagi plant to reveal latent fingerprints from different non-porous surfaces (cardboard, plain glass, aluminum foil sheet, China Dish, Plastic, and Switch). The effect of three variables on activated carbon production was investigated. These variables were the impregnation ratio (the weight ratio of KOH: dried raw material), the activation temperature, and the activation time. The effect factors were investigated using Central Composite Design (CCD) softwa

The main purpose of this investigation is to evaluate the concentrations of six essential metals (Na⁺, Mg²⁺, K⁺, Ca²⁺, Fe²⁺ and Zn²⁺) in saffron and a farm soil using the neutron activation analysis (NAA) as a nuclear spectrometry method. The stratified random sampling method was used here. The NAA results showed the well uptake of Mg²⁺, K⁺, Ca²⁺, Fe²⁺, and Zn²⁺ in saffron, which is lower than the toxicity range. Based on the contamination factor and geoaccumulation index, soil contamination levels were determined uncontaminated by Zn, moderately contaminated by Na⁺ and Fe²⁺, and strongly contamin

This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and ge

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

Segmentation is the process of partition digital images into different parts depending on texture, color, or intensity, and can be used in different fields in order to segment and isolate the area to be partitioned. In this work images of the Moon obtained through observations in Astronomy and space dep. College of science university of Baghdad by ( Toward space telescopes and widespread used of a CCD camera) . Different segmentation methods were used to segment lunar craters. Different celestial objects cause craters when they crash into the surface of the Moon like asteroids and meteorites. Thousands of craters appears on the Moon's surface with ranges in size from meter to many kilometers, it provide insights into the age and geology