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 Convolutional Neural Network (CNN) has been chosen as a better option for the training process because it produces a high accuracy. The final accuracy has reached 91.18% in five different classes. The results are discussed in terms of the probability of accuracy for each class in the image classification in percentage. Cats class got 99.6 %, while houses class got 100 %.Other types of classes were with an average score of 90 % and above.
The Flanagan Aptitude Classification Tests (FACT) assesses aptitudes that are important for successful performance of particular job-related tasks. An individual's aptitude can then be matched to the job tasks. The FACT helps to determine the tasks in which a person has proficiency. Each test measures a specific skill that is important for particular occupations. The FACT battery is designed to provide measures of an individual's aptitude for each of 16 job elements.
The FACT consists of 16 tests used to measure aptitudes that are important for the successful performance of many occupational tasks. The tests provide a broad basis for predicting success in various occupational fields. All are paper and pen
... Show MoreIn this paper a dynamic behavior and control of a jacketed continuous stirred tank reactor (CSTR) is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.
The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.
The results s
... Show MoreAbstract
The aim of the present research is to identify the test wisdom and the preoccupation with learning and psychological tension among postgraduate students at the University of Samarra according to the variables of the department, gender, age, and employee or non-employee, and revealing the relationship between the test wisdom and the preoccupation with learning and psychological tension. The research sample consisted of (75) students randomly selected from postgraduate students at the college of Education. The researcher applies test –wisdom of (Mellman & Ebel) and measurement of preoccupation with learning prepared by (Al-zaabi 2013) also, the researcher used the scale of t
... Show MoreThe Study aims at evaluating the efficiency of the regional transportation net in Al-mahmoodiya Qadaa center. The bus station of the Qadaa center is suffering from heavy traffic jam, which is due to the ongoing movement of the adjacent provinces, particularly the small cities. They vary in the degree of their link by the regional transportation net that links the province with the centers of big cities. That affects the traffic flow of the civilians of these cities and their daily activities in hierarchical way To achieve the purpose of the study, a questionnaire has been constructed to collect data through selecting a random sample including the passengers who are coming to the bus station in Al-Mahmoodiya center to know the flo
... Show MoreOnline learning is not a new concept in education, but it has been used extensively since the Covid-19 pandemic and is still in use now. Every student in the world has gone through this learning process from the primary to the college levels, with both teachers and students conducting instruction online (at home). The goal of the current study is to investigate college students’ attitudes towards online learning. To accomplish the goal of the current study, a questionnaire is developed and adjusted before being administered to a sample of 155 students. Additionally, validity and reliability are attained. Some conclusions, recommendations, and suggestions are offered in the end.
Abstract
The image of the soldier, as a hero who sacrifices everything to defend his
country and values, is no longer depicted in modern drama. With two World Wars
and many regional wars and civil wars, the soldier becomes a victim, not a hero.
Authors present the character of the soldier as a man who suffers a lot as he is
victimized by his own government and its politics that forces him to be in such a
position. Dramatists express their views about race, oppression and war through
their characters, such as the character of the soldier, as in the two selected plays for
this research: The Hostage by Brendan Behan and A Soldier's Play by Charles
Fuller.
The Hostage depicts, through its events, the Irish oppre
In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal
... Show MoreThis paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to
... Show MoreObjective: To assess the clinical learning environment and clinical training for students' in maternal and child
health nursing.
Methodology: A descriptive study was conducted on non probability sample (purposive) of (175) students' in
Nursing College/ University of Baghdad for the period of June 19th to July 18th 2013. A questionnaire was used as a
tool of data collection to fulfill with objective of the study and consisted of three parts, including demographic,
clinical learning environment and clinical training for students' in maternal and child health nursing. Descriptive
statistical analyses were used to analyze the data.
Results: The results of the study revealed that the 65.1% of student at age which ranged b