This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being conducted to analyze and understand the strengths and weakness of the proposed new method. This research shows that spectral indices are easy and accurate tool for rapid mapping of paddy rice fields in complicated environment where urban features are dominated. The outcomes of this research could help mapping and decision makers to progress their productivity and strategic plans for better management of rice fields.
The efficiency of Nd:YAG laser radiation in removing debris and smear layer from prepared root
canal walls was studied. Fifty-seven human extracted single rooted anterior teeth were divided into three
groups. A group that was not lased is considered as a control group. The remaining teeth were exposed to
different laser parameters regarding laser energy, repetition rate and exposure time. For the case of the set of
parameters of 7 mJ laser energy, the cleaning was maximum at 3 p.p.s. repetition rate for 3 seconds exposure
time for, the coronal, middle and apical thirds. Above and below this energy level, there was an overdose
(melting) or under dose (no effect). Nevertheless for 10mJ laser energy case, the cleaning effi
In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor
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This research examines the phenomenon of the Arabic language repeated in the Qur'an and poetry, as some morphological formulas are valid in their uses and indications in more than one way. search).
Objective: To determine the effectiveness of the Nursing Management Education Program upon the Nurse
Managers' Knowledge about planning in Nursing Management at Baghdad City Hospitals.
Methodology: A Quasi-experimental study in which a purposive "non-probability" sample of (50) Nurse
Managers was selected from Baghdad City Hospitals. These Managers were divided into two equal groups of
(25) Nurse Managers for each (study and control ones). A questionnaire was developed as a tool for data
collection. A pilot study was carried out to test the reliability of the questionnaire for the period from April 2nd to
June 20th 2007. The pre-post test approach was applied to the study and control groups as mean for the quasiexperime
The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabet
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This research is a study of the difficulties of learning the Arabic language that faces Arabic language learners in the Kurdistan Region, by revealing its types and forms, which can be classified into two categories:
The first type has difficulties related to the educational system, the source of which is the Arabic language itself, the Arabic teacher or the learner studying the Arabic language or the educational curriculum, i.e. educational materials, or the educational process, i.e. the method used in teaching.
The second type: general difficulties related to the political aspect, the source of which is the policy of the Kurdistan Regional Government in marginalizing the Arabic language and replacing the forefront of th
... Show Moreالناصر، عامر عبد الرزاق عبد المحسن والكبيسي، صلاح الدين عواد كريم. 2018. إمكانية تبني الحوسبة السحابية الهجينة في الجامعات العراقية : دراسة تحليلية باستخدام أنموذج القبول التكنولوجي. مجلة الإدا
Attention increased to the topic of academic accreditation by the university as a modern philosophy by which to improve its performance and provide high-quality education. Universities and colleges in general and Iraqi universities and colleges in particular have begun interest in accreditation and desire to get it. So starting from the pursuit of the Administration and Economics College / Baghdad University in obtaining accreditation of Association to Advance Collegiate Schools of Business (AACSB) The research is present which aims to determine the level of application (AACSB) International standards at the College of Administration and Economics / Baghdad University in preparation to get its accreditation in the future. Researc
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