Intense electromagnetic phenomena occurring on the Sun’s surface give rise to solar flares. Energetic solar flares have the potential to reach Earth, causing significant interference with telecommunication systems. Particularly powerful solar events can even disrupt satellite and ground communication infrastructure, posing a substantial risk of extensive damage. To mitigate these risks, comprehensive monitoring systems and robust forecasting techniques are essential for early detection and warning. This research proposes an approach utilizing the extreme gradient boosting (XGBoost) algorithm for solar flare classification. Recognizing that the performance of XGBoost is heavily influenced by appropriate hyperparameter selection, a modified metaheuristic algorithm is introduced to optimize the network’s hyperparameters. To evaluate the efficacy of the proposed methodology, a real-world dataset is utilized, and a thorough comparative analysis is conducted, encompassing several contemporary algorithms that address the same solar flare classification task under identical conditions. The objective is to identify the advantages and strengths of the proposed modified metaheuristic approach in comparison to existing methods.
IT governance (ITG) is the processes that ensure the effective and efficient use of IT in enabling an organization to achieve its goals. ITG ensures the organization, its data, and its people are protected, while reducing risk and syncing with business objectives. This is achieved through the appropriate IT policies, processes, and procedures, that must be applied consistently across the organization. This paper presents the way forward for adopting the ITG. It introduces the IT Security Office proposal that helps any Libyan organization or institution planning to deploy IT Governance. The proposal is based on the need for any organization to secure; according to the international IT policy and standards, (1) the current use, operation, and implementation of its Information Technology (IT) systems, and (2) the vision of the organization to adopt for example electronic administrative and financial systems and starting its digital transformation journey. This document is organized as follows. First, the proposal introduces IT and its Security Office function and adoption. Then, the proposal specifies the administrative hierarchy of the office in the organization chart and why we need it. Third, it defines the working conditions of the office in such an organizational chart. Fourth, the office duties and responsibilities are described. Finally, the proposal gives recommendations of how an organization could start working in this office and highlights some benefits of implementing such approach.
Many outage probability events have recently been recorded in Libya because of rain attenuation impact, especially at millimetre wave (mmWave) spectrum in terrestrial and satellite links. Therefore, accurate prediction of rain attenuation phenomena is highly recommended to mitigate outages due to rain fade. Rainfall statistical data measured for long-term data of 30 years were collected from five locations in Libya. Collected data were analysed and processed to convert into one–minute rain rate cumulative distribution. The model proposed by ITU-R has been utilised to predict and investigate rain fade based on converted 1-min rain rate data for sites in various climate regions in Libya in the zenith paths of the Hylas 2 satellite. The impact of different parameters such as frequency (GHz), satellite elevation (degrees), polarisation, and percentage of the year on rain fade prediction has been tested. Additionally, the essential properties of link performance have been investigated in determining dependable fade margin. The impact of rain attenuation at 28 GHz was considered for performance analysis at Benina (R0.01
The Holy Qur'an is the oldest comprehensive Arabic book of recommendation for Muslims worldwide. Provide knowledge and information used in various ways. People often utilize the Holy Qur'an, considered a reliable and trustful legislated text, for education and to meet their needs and inquiries of the Muslim community. Like extracting an answer span from the provided passage, The Qur'an has the potential to captivate the curiosity of non-Muslims and propel them towards exploring a vast array of topics and pursuing answers. Over the past few years, Question Answering (Q.A.) has drawn much attention from the NLP community. Researchers and experts have developed various Qur'anic Question Answering (QAA) systems. Nevertheless, the main challenge in the Arabic language is the need for more resources, making it difficult to provide highly accurate Arabic QA systems. The first Qur’an Question Answering shared task workshop, “Qur’an QA 2022,” aims to promote state-of-the-art research on Qur'anic question answering QA in general and machine reading comprehension MRC in particular. It aims to develop models to extract questions answering the holy Qur’an passages. This research paper motivated by this task, suggests an ensemble learning model based on Arabic-supported versions of BERT, which will be implemented using the KNIME platform. We aim to use this model for Arabic Question Answering.; as a result, we get 0.488 for the AUC and 0.946 for accuracy.
This paper presents the development of an advanced system designed to efficiently process Arabic queries in today’s data-driven landscape. By using the T5 sequence-to-sequence model developed by Google and fine-tuning it specifically for transforming textual and verbal input into SQL queries, the system becomes adept at accurately comprehending and interpreting Arabic queries. The resulting system serves as a user-friendly tool that automates the generation of SQL queries. Users can input their queries in written or recorded Arabic utterances, eliminating the need for manual translation and query construction. This involved fine-tuning T5 models on a SQL dataset, splitting the dataset, tokenizing it, and setting training parameters. The implementation phase included loading the fine-tuned model, which incorporated PICARD to generate valid queries effectively. This paper also explores the impact of Arabic translation on the performance and accuracy of the model. The optimal testing on test set accuracy achieved was 63.11
