Internet of Things (IoT) devices often operate with limited resources while interacting users and their environment, generating a wealth data. Machine learning models interpret such sensor data, enabling accurate predictions informed decisions. However, the sheer volume data from billions can overwhelm networks, making traditional cloud processing inefficient for IoT applications. This paper presents comprehensive survey recent advances in models, architectures, hardware, design requirements...

Brain tumors are a leading cause of death globally, with numerous types varying in malignancy, and only 12% adults diagnosed brain cancer survive beyond five years. This research introduces hyperparametric convolutional neural network (CNN) model to identify tumors, significant practical implications. By fine-tuning the hyperparameters CNN model, we optimize feature extraction systematically reduce complexity, thereby enhancing accuracy tumor diagnosis. The critical include batch size, layer...

Rapid scaling of using the Internet Things (IoT) technology has been seen recently in numerous applications healthcare to deliver proper services. This was motivated by declining size and cost employed IoT devices. Developing such well investigated literature; however, few studies have explored factors influencing its adaptation setting. In this study, we investigate core that influence acceptance for Healthcare Purposes Kingdom Saudi Arabia (KSA). Accordingly, a theoretical framework, based...

This paper introduces a novel approach to improve security in dynamic network slices for 5G networks using Graph-based Generative Adversarial Networks (G-GAN). Given the rapidly evolving and adaptable nature of slices, traditional mechanisms often fall short providing real-time, efficient, scalable defense mechanisms. To address this gap, study proposes use G-GAN, which combines strengths (GANs) Graph Neural (GNNs) adaptive learning anomaly detection environments. The proposed utilizes GAN...

Phishing attacks remain a significant cybersecurity threat in the digital landscape, leading to development of defense mechanisms. This paper presents thorough examination Artificial Intelligence (AI)-based ensemble methods for detecting phishing attacks, including websites, emails, and SMS. Through screening research articles published between 2019 2023, 37 relevant studies were identified analyzed. Key findings highlight prevalence such as AdaBoost, Bagging, Gradient Boosting attack...

As the fifth-generation (5G) wireless networks continue to advance, concept of network slicing has gained significant attention for enabling provisioning diverse services tailored specific application requirements. However, security concerns associated with pose challenges that demand comprehensive exploration and analysis. In this paper, we present a systematic literature review critically examines existing body research on machine learning techniques securing 5G slicing. Through an...

The search complexity for partial transmit sequence (PTS) and selective mapping (SLM) techniques increases exponentially with the number of sub-blocks, necessitating a comprehensive over all possible combinations phase-weighting variables. This paper proposes novel complex system modeling approach PTS SLM in an Orthogonal Time Frequency Space (OTFS) system, utilizing phase factors sub-block partition scheme. We describe OTFS that achieves low computational identifying optimal reducing...

The Internet of Medical Things (IoMT) refers to interconnected medical systems and devices that gather transfer healthcare information for several applications. Smart leverages IoMT technology improve patient diagnosis, monitoring, treatment, providing efficient personalized services. Privacy-preserving Federated Learning (PPFL) is a privacy-enhancing method allows collaborative training through distributed data sources while ensuring privacy protection keeping the decentralized. In field...

Currently, Text-to-Speech (TTS) or speech synthesis, the ability of complex system to generate a human-like sounding voice from written text, is becoming increasingly popular in processing various systems. TTS artificial generation human speech. A classical translates language text into waveform. Several English systems produce human-like, mature, and natural synthesizers. On other hand, languages, such as Arabic, have just been considered. The present Arabic synthesis solution low quality...

<title>Abstract</title> Multimodal generative artificial intelligence is revolutionizing critical domains, including education, healthcare, business, and entertainment. This article presents a comprehensive umbrella review of prominent surveys, reviews, SLRs on advances in AI teaching learning, synthesizing its applications, benefits, challenges, implications. We applied the systematic literature (SLR) protocol PRISMA framework to guide our search methodology screen relevant studies ensure...

Automatic noise-robust speaker identification is essential in various applications, including forensic analysis, e-commerce, smartphones, and security systems. Audio files containing suspect speech often include background noise, as they are typically not recorded soundproof environments. To this end, we address the challenges of noise robustness accuracy An ensemble approach proposed combining two different neural network architectures an RNN DNN using softmax. This enhances system’s...

Every healthcare system in the world experiences a variety of challenges as well opportunities they attempt to deliver services that are accessible, efficient, and, most importantly, equitable. This review presents general areas interest health systems and implementation sciences while appreciating trends, barriers, variations, innovations influencing practices producing improved patients' status. It includes topics like access/travel care, service quality, payment/reimbursement processes,...

There is a global trend towards the use of 'Internet Things' technology in smart applications like cities, energy engagement and others.However, this creates many electronic risks because IoT technical technological nature.With multiple e-risks forms types, it becomes necessary that each country develops protective measures so as to reduce expected level risk.Such can take form actions via legislatures or educating users companies about seriousness upcoming technology.This be done by...