The change in the size of the droplets during the pesticide application process could have a negative impact on the percentage of drift or the losses of pesticides to the environment. One of the factors that could affect the droplet size produced from a single nozzle is the internal design of the nozzle itself, in addition to the wear of the nozzle orifice as a result of the usage time. In this research, three types of nozzles with different internal designs were used (Turbo TeeJet (TT), Turbo TwinJet (TTj 6011003), and Drift Guard (DG 11003)). The nozzles were subjected to an accelerated wear test for one hundred hours, and different droplet size parameters (Dv 0.1, Dv 0.5, Dv 0.9),
هدفت هذه الدراسة إلى تحليل نتائج الاختبار الوطني الموحد الذي تطبقه وزارة التربية والتعليم الفلسطينية في مادة الرياضيات لطلبة الصف الثامن الأساسي في المدارس الحكومية في محافظة طولكرم، وذلك لمعرفة مستوى الطلبة على هذا الاختبار في ضوء متغيرات الجنس والمنطقة التعليمية ونوع المدرسة، ومعرفة علاقة التحصيل على هذا الاختبار بتحصيل الطلبة المدرسي والمعدل العام. ولتحقيق ذلك تم تحليل درجات (3218) طالباً وطالبة؛ وهم ي
... Show MoreThis study proposes a pioneering Ethical Artificial Intelligence (EAI) framework for advancing sustainable development in Iraq by integrating eight multidimensional sustainability indicators—administrative, technological, economic, environmental, social, legal, security, and governance. Utilizing data from 60 completed development projects, the framework combines SPSS statistical analysis, the SMART-AI model, and Artificial Neural Networks (ANN) to identify key determinants of project success and failure. Results reveal a 37% project failure rate, with administrative and technological deficiencies emerging as the most influential predictors. The SMART-AI model achieved an accuracy of 91.3% using stratified k-fold cross-validation. A bilin
... Show MoreWith the increasing demands to use remote sensing approaches, such as aerial photography, satellite imagery, and LiDAR in archaeological applications, there is still a limited number of studies assessing the differences between remote sensing methods in extracting new archaeological finds. Therefore, this work aims to critically compare two types of fine-scale remotely sensed data: LiDAR and an Unmanned Aerial Vehicle (UAV) derived Structure from Motion (SfM) photogrammetry. To achieve this, aerial imagery and airborne LiDAR datasets of Chun Castle were acquired, processed, analyzed, and interpreted. Chun Castle is one of the most remarkable ancient sites in Cornwall County (Southwest England) that had not been surveyed and explored
... Show MoreThe present research aims to identify and define the basic dimensions of the information management strategy and the administrative creativity in the Faculty of Management and Economics / the University of Kirkuk, as well as the role played by the dimensions of the information technology management strategy in achieving the administrative innovation in the college and the research problem was formulated in several questions. The research problem was formulated in several questions centered on the correlation between the research variables, and the research was based on a major hypothesis and five sub-hypotheses emerged from which it was subjected to several tests to ensure its validity. The researcher used the descriptive-analyti
... Show MoreThree-dimensional (3D) reconstruction from images is a most beneficial method of object regeneration by using a photo-realistic way that can be used in many fields. For industrial fields, it can be used to visualize the cracks within alloys or walls. In medical fields, it has been used as 3D scanner to reconstruct some human organs such as internal nose for plastic surgery or to reconstruct ear canal for fabricating a hearing aid device, and others. These applications need high accuracy details and measurement that represent the main issue which should be taken in consideration, also the other issues are cost, movability, and ease of use which should be taken into consideration. This work has presented an approach for design and construc
... Show MoreRecommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n
... Show MoreThe aim of this paper is to present a new methodology to find the private key of RSA. A new initial value which is generated from a new equation is selected to speed up the process. In fact, after this value is found, brute force attack is chosen to discover the private key. In addition, for a proposed equation, the multiplier of Euler totient function to find both of the public key and the private key is assigned as 1. Then, it implies that an equation that estimates a new initial value is suitable for the small multiplier. The experimental results show that if all prime factors of the modulus are assigned larger than 3 and the multiplier is 1, the distance between an initial value and the private key
... Show MoreFace recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni
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