Abstract:

The issues related to foreign trade is a broad field for discussions and captures the interest of economists for their contribution to the process of economic development in the economies of the countries, especially developing ones. The imports of goods and services in foreign trade constitute an important part of the local by which the economy gets goods and services that the economy cannot produce because of the incompetent base of production. Further, the demand function of imports occupied a good deal of the attention of researchers in the field of international economics for which agricultural imports constitute an important part. The reason for the interest in the subject is due to its im

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

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

The learner has face difficult in learning if not accompanied by strong motivation and directed towards the goals that set for himself,as the type of goals set by the learner for himself is behind the difference in achievement of the tasks and levels of learning, and these goals are directed and determine his behavior Academic in the way of his study and his direction towards the lecture and colleagues.

Current research aims:

• Build tools for thegoal orientations
• Measuring the goal orientations for the university studentsaccording to variables (type/class/specialization).

In order to achieve the objectives of the research, a tool was constructed for the (the Goal orientation), and the psych

The study consisted in the development and use of a practical method to detect and
monitor, analyze and produce maps of changes in land use and land cover in the district of
Mahmudiya in Baghdad during the period 1990-2007 using the applications of remote sensing
techniques and with the assisstant of geographic information systems (GIS),as a valuable
contribution to land degradation studies.
This study is based maiuly on the processing on two subsets of landsat5 TM images picked up
in August 1990 and 2007 respectively in order to facilitate comparision and were thengeometrically and radiometrcally calibrated ,to used for digital classification purposes using
maximum liklihoods classification or six spectral bands of

An experimental study was carried out for an evaporative cooling system in order to investigate the effect of using an aluminum pad coated with fabric polyester. In the present work, it was considered to use a new different type of cooling medium and test its performance during the change in the wet-bulb temperature and dry-bulb temperature of the supply air outside of the pad, the relative humidity of the supply air, the amount of air supplied (300-600) CFM and also the change of the amount of circulated water (1.75, 2.5, 4.5) liter per minute. A decrease in the WBT of the air was obtained, whereas the WBT of the air entering the pad was 26.5 . In contrast, the WBT of the outside air had reached 23  even though eva

Idiomatic expressions in Russian journalism make one important borrowed means for making a dialogue with the receiver's intellect in so far as it has the distinct feature of  having clarity and exactness of meaning. The meaning is seen as a shortcut for covering a series of concepts and details so as to arrive at the intended meaning. This is done by stimulating the reader by the use of certain clear idioms. The use of such idioms in a journalistic text is not for a linguistic purpose only, but it is a cultural and social phenomenon reflecting the type of current changes in the society and it aims at discoursing with the reader's mind. This paper is a practi

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca