Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

The use of Conservatism  significant impacts on the financial statements and thus on financial reporting which is produced by these lists so Rate Some of the professionals that the principle of accounting while Rate of others as a constraint, and brought this category based on the uses of this restriction sometimes used the accountant this restriction and especially with the uncertainties in the Sometimes it may collide with some of the cases in which the accountant may be forced to leave in custody as a result of emergence of economic events that gave rise to rights or future commitments should be disclosed.

The emergence in custody mainly was due to the uncertainty and its essence is to report on a

Purpose: To compare the antibacterial-enhancing efficacy of aloe vera and honey in salicylic acid topical formulations against acne. Method: Six formulations containing 5 % salicylic acid were developed as creams and gels as follows: Formulations S, V and H were creams containing salicylic acid alone (S), salicylic acid with 28 % aloe vera (V), and salicylic acid with 10 % honey (H). Formulations J, M, and B were gels containing salicylic acid alone (J), salicylic acid with aloe vera 20 % (M) and salicylic acid with 12 % honey (B). Each formula was evaluated for colour, odour, pH, viscosity, spreadability, and stability under different temperatures (25, 30, and 60oC) and times (1 hour, 1 day, and 1 week). Furthermore, antibacterial

This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.

With the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the

أثبتت الشبكات المحددة بالبرمجيات (SDN) تفوقها في معالجة مشاكل الشبكة العادية مثل قابلية التوسع وخفة الحركة والأمن. تأتي هذه الميزة من SDN بسبب فصل مستوى التحكم عن مستوى البيانات. على الرغم من وجود العديد من الأوراق والدراسات التي تركز على إدارة SDN، والرصد، والتحكم، وتحسين QoS، إلا أن القليل منها يركز على تقديم ما يستخدمونه لتوليد حركة المرور وقياس أداء الشبكة. كما أن المؤلفات تفتقر إلى مقارنات بين الأدوات والأ

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,