Wildfire risk has globally increased during the past few years due to several factors. An efficient and fast response to wildfires is extremely important to reduce the damaging effect on humans and wildlife. This work introduces a methodology for designing an efficient machine learning system to detect wildfires using satellite imagery. A convolutional neural network (CNN) model is optimized to reduce the required computational resources. Due to the limitations of images containing fire and seasonal variations, an image augmentation process is used to develop adequate training samples for the change in the forest’s visual features and the seasonal wind direction at the study area during the fire season. The selected CNN model (Mob

Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, an

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

The research addresses the importance of reading and writing for sura Al-alaq and Al-qalam as they represent the main sources for all the sciences as well as ethical values. The researcher seeks to define the educational and ethical values in these two texts which related to reading and writing. To do this, the author went through different relevant literature to show the similarities and related points between them, she also shows the significant of reading and writing and the learning and teaching worth to be consider. The result revealed that the both texts assert on the educational and ethical values, and the vital role of reading and writing.  

Physical measurements are one of the basic factors that affect the performance of the goalkeeper, especially when confronting fixed kicks that require special skills such as the reaction and accuracy in concentration, and with technological development artificial intelligence has become an effective tool for analyzing mathematical data that is difficult to discover in traditional methods The study aims to employ techniques Artificial intelligence to study the relationship between physical measurements and the accuracy of confronting the fixed kicks of goalkeepers in football. This study will contribute to providing a deeper understanding of physical factors that affect the performance of goalkeepers, in addition to designing dedicat

Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn

In this study, the effect of pumping power on the conversion efficiency of nonlinear crystal (KTP) was investigated using laser pump-power technique. The results showed that the higher the pumping power values, the greater the conversion efficiency (η) and, as the crystal thickness increases within limitations, the energy conversion efficiency increases at delay time of (0.333 ns) and at room temperature. Efficiency of 80% at length of KTP crystal (L = 1.75 X 10^-3 m) and P_in = 28MW, and also, compare the experimental results with numerical results by using MATLAB program. 

With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an

Reservoir quality assessment is important for detecting hydrocarbon-bearing zones and guiding future enhancement strategies. This study presents a detailed petrophysical evaluation of the Mishrif Formation in the Buzurgan Oilfield, which was selected due to its strategic value through its significant remaining reserves which making it an ideal candidate for advanced evaluation techniques. This study aims for shale content, porosity, permeability, water saturation, net to gross, and lithology determination. Well log and core data were used together to establish accurate property estimations. Permeability prediction through conventional methods, like core permeability-porosity correlations, was highly dispersive due to the heterogenei