Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

In this paper, a new equivalent lumped parameter model is proposed for describing the vibration of beams under the moving load effect. Also, an analytical formula for calculating such vibration for low-speed loads is presented. Furthermore, a MATLAB/Simulink model is introduced to give a simple and accurate solution that can be used to design beams subjected to any moving loads, i.e., loads of any magnitude and speed. In general, the proposed Simulink model can be used much easier than the alternative FEM software, which is usually used in designing such beams. The obtained results from the analytical formula and the proposed Simulink model were compared with those obtained from Ansys R19.0, and very good agreement has been shown. I

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Perimenopausal bleeding, is a very common problem, which is an alarming symptom for both; women and their doctors because of the rising fears of cellular changes or tumor of endometrium. In our study we tried to prove that collecting endometrial samples using the outpatient method of Pipelle is as effective as collecting the endometrial samples in the traditional method of Dilation and Curettage (DandC) in operation theatre which necessitates general anesthesia. Ninety four patients more than 40 years old were included in the study, all of them were complaining of abnormal uterine bleeding (pregnant ladies and ladies using hormonal contraception were excluded from the study) and endometrial samples were collected first in outpatient

Gross domestic product (GDP) is an important measure of the size of the economy's production. Economists use this term to determine the extent of decline and growth in the economies of countries. It is also used to determine the order of countries and compare them to each other. The research aims at describing and analyzing the GDP during the period from 1980 to 2015 and for the public and private sectors and then forecasting GDP in subsequent years until 2025. To achieve this goal, two methods were used: linear and nonlinear regression. The second method in the time series analysis of the Box-Jenkins models and the using of statistical package (Minitab17), (GRETLW32)) to extract the results, and then comparing the two methods, T

Background: Penetrating Neck Injuries (PNI) management represents a challenge to most surgeons in civilian trauma, in weighing selective versus mandatory exploration of all cases in different circumstances. Data are encouraging surgeons to adopt the former approach.Objectives: The study aims to assess the selective approach in our war and terror time events in Al-Yarmouk teaching hospital.Type of the study:A retrospective study. Methods: Data of patients presented to the Thoracic and Vascular ward in Al-Yarmouk teaching hospital with PNI were assessed retrospectively, from March 2013 to March 2015, and analyzed for epidemiology, mechanism of trauma, management methods, associated organ injuries, complications and mortality. Results: Amon

Aggression is a negative form of an anti-social behavior. It is produced because of a particular reason, desire, want, need, or due to the psychological state of the aggressor. It injures others physically or psychologically. Aggressive behaviors in human interactions cause discomfort and disharmony among interlocutors. The paper aims to identify how aggressive language manifests itself in the data under scrutiny in terms of the pragmatic paradigm. Two British literary works are the data; namely, Look Back in Anger by John Osborne (1956), and The Birthday Party by Harold Pinter (1957). This paper endeavors to answer the question of how aggressive language is represented in literature pragmatically? It is hoped to be significant to

A second-order sliding mode control is used for high-order uncertain plants using equivalent control approach to improve the performance of control systems. They combine backstepping with quasi-continuous controller and twisting controllers. This paper considers a two of the most popular controllers that are used to solve the nonlinearities problem which are the backstepping quasi-continuous control (BQCC) and backstepping twisting controllers to control the angular velocity of a hydraulic motor to improve tracking performance and robustness to uncertainties. For the system dynamics, a linear state feedback with suitable high gain was designed as the virtual controller, where steady state error can be made arbitrarily small according to the

This paper presents a vibration suppression control design of cantilever beam using two piezoelectric ‎patches. One patch was used as ‎an actuator element, while the other was used as a sensor. The controller design was designed via the balance realization reduction method to elect the reduced order model that is most controllable and observable. ‎the sliding mode observer was designed to estimate six states from the reduced order model but three states are only used in the control law. Estimating a number of states larger than that used is in order to increase the estimation accuracy. Moreover, the state ‎estimation error is proved bounded. An ‎optimal LQR controller is designed then using the ‎estimated states with the slid

The purpose of this research is defining the main factors influencing on decision of management system on sensitive data in cloud. The framework is proposed to enhance management information systems decision on sensitive information in cloud environment. The structured interview with several security experts working on cloud computing security to investigate the main objective of framework and suitability of instrument, a pilot study conducts to test the instrument. The validity and reliability test results expose that study can be expanded and lead to final framework validation. This framework using multilevel related to Authorization, Authentication, Classification and identity anonymity, and save and verify, to enhance management