Precision medicine has gained considerable popularity since the “one-size-fits-all” approach did not seem very effective or reflective of the complexity of the human body. Subsequently, since single-omics does not reflect the complexity of the human body's inner workings, it did not result in the expected advancement in the medical field. Therefore, the multi-omics approach has emerged. The multi-omics approach involves integrating data from different omics technologies, such as DNA sequencing, RNA sequencing, mass spectrometry, and others, using computational methods and then analyzing the

This paper tackles the problem of generating pho-torealstic images of synthetically rendered human avatar faces from computer graphics engines, our approach leverages the high capabilities of generative models as StyleGAN that can generate high quality human faces that are hard to distinguish from real human faces images. We present a framework that effectively bridges the gap between synthetic and real domain through Single shot GAN inversion that maps the synthetic image into the real latent space of StyleGAN. Benchmarks and Quantitative results show that our method demonstrate significant

Capturing the diverse microbiota from healthy and/or stress resilient plants for further preservation and transfer to unproductive and pathogen overloaded soils, might be a tool to restore disturbed plant-microbe interactions. Here, we introduce Aswan Pink Clay as a low-cost technology for capturing and storing the living root microbiota. Clay chips were incorporated into the growth milieu of barley plants and developed under gnotobiotic conditions, to capture and host the rhizospheric microbiota. Afterward, it was tested by both a culture-independent (16S rRNA gene metabarcoding) and

The fast expansion of the Internet of Things (IoT) in the technology and communication industries necessitates a continuously updated cyber-security mechanism to keep protecting the systems' users from any possible attack that might target their data and privacy. Botnets pose a severe risk to the IoT, they use malicious nodes in order to compromise other nodes inside the network to launch several types of attacks causing service disruption. Examples of these attacks are Denial of Service (DoS), Distributed Denial of Service (DDoS), Service Scan, and OS Fingerprint. DoS and DDoS attacks are the

Mobile Ad hoc networks (MANETs) facilitate the communication of devices with a limited communication range. A MANET can be described as a decentralized network with a constantly changing topology. This makes it vulnerable to different attacks. The black hole is one of the most dangerous attacks in MANETs. This paper discusses the Blackhole attack in a random mobility environment and analyses its impact on MANETs using several parameters for single and multiple connections. © 2022 IEEE.

Arabic is one of the world's richest languages, with a diverse range of dialects based on geographical origin. In this paper, we present a solution to tackle subtask 1 (Country-level dialect identification) of the Nuanced Arabic Dialect Identification (NADI) shared task 2022 achieving third place with an average macro F1 score between the two test sets of 26.44%. In the preprocessing stage, we removed the most common frequent terms from all sentences across all dialects, and in the modeling step, we employed a hybrid loss function approach that includes Weighted cross entropy loss and Vector

Visual Question Answering (VQA) systems have achieved remarkable advancements by combining text-based question answering with image analysis. This integration has resulted in the creating of machines that can comprehend and address questions related to visual content. Despite these technological developments, a notable lack of VQA solutions specifically designed for the Arabic language remains. This gap persists even with the significant progress made in deep learning techniques and the development of Large Language models (LLMs). Our research introduces ArabicQuest, an innovative chatbot

The need for a comprehensive consolidated guide for R packages and tools that are used in microbiome data analysis is significant; thus, we aim to provide a detailed step-by-step dissection of the most used R packages and tools in the field of microbiome data integration and analysis. The guideline aims to be a user-friendly simplification and tutorial on five main packages, namely phyloseq, MegaR, DADA2, Metacoder, and microbiomeExplorer due to their high efficiency and benefit in microbiome data analysis. © 2023, The Author(s), under exclusive license to Springer Science+Business Media, LLC

Sentiment analysis is a common and challenging task in natural language processing (NLP). It is a widely studied area of research; it facilitates capturing public opinions about a topic, product, or service. There is much research that tackles English sentiment analysis. However, the research in the Arabic language is behind other high-resource languages. Recently, models such as bidirectional encoder representations from transformers (BERT) and generative pre-trained transformer (GPT) have been widely used in many NLP tasks; it significantly improved performance in NLP tasks, especially

In an attempt to bridge the semantic gap between language understanding and visuals, Visual Question Answering (VQA) offers a challenging intersection of computer vision and natural language processing. Large Language Models (LLMs) have shown remarkable ability in natural language understanding; however, their use in VQA, particularly for Arabic, is still largely unexplored. This study aims to bridge this gap by examining how well LLMs can improve VQA models. We use state-of-the-art AI algorithms on datasets from multiple fields, including electric devices, Visual Genome, RSVQA, and ChartsQA