The sixth-generation (6G) technology of mobile networks will establish new standards to fulfill unreachable performance requirements by fifth-generation (5G) networks. This is due the high for more intelligent network, ultra-lower latency, extreme network communication speed, and supporting massive number various connected applications. In long term, convergence business developments with platforms, as initiated 5G, exaggerate highlight areas where 5G's capabilities fall short requirements....

Brain tumors (BTs) are spreading very rapidly across the world. Every year, thousands of people die due to deadly brain tumors. Therefore, accurate detection and classification essential in treatment Numerous research techniques have been introduced for BT as well based on traditional machine learning (ML) deep (DL). The ML classifiers require hand-crafted features, which is time-consuming. On contrary, DL robust feature extraction has recently widely used purposes. this work, we propose a...

Breast cancer (BC) is a type of tumor that develops in the breast cells and one most common cancers women. Women are also at risk from BC, second life-threatening disease after lung cancer. The early diagnosis classification BC very important. Furthermore, manual detection time-consuming, laborious work, and, possibility pathologist errors, incorrect classification. To address above highlighted issues, this paper presents hybrid deep learning (CNN-GRU) model for automatic BC-IDC (+,−) using...

Ensuring a seamless connection during the mobility of various User Equipments (UEs) will be one major challenges facing practical implementation Fifth Generation (5G) networks and beyond. Several key determinants significantly contribute to numerous challenges. One most important is use millimeter waves (mm-waves) as it characterized by high path loss. The inclusion types small coverage Base Stations (BSs), such Picocell, Femtocell drone-based BSs another challenge. Other issues include Dual...

Drones will be a significant part of future mobile communication networks, serving as users or acting base stations at sky. Although they provide several solutions related to networks and other non-communication services, drones also possess numerous challenges, especially when it comes their handover management. Unlike terrestrial are devices that move in three-dimension (3D) environment, which further complicates mobility issues. Therefore, this paper provides an overview on the management...

Improving energy efficiency is crucial for smart factories that want to meet sustainability goals and operational excellence. This study introduces a novel decision-making framework optimize in manufacturing environments, integrating Intuitionistic Fuzzy Sets (IFS) with Multi-Criteria Decision-Making (MCDM) techniques. The proposed approach addresses key challenges, including reducing carbon footprints, managing operating costs, adhering stringent environmental standards. Eight essential...

Ensuring a reliable and stable communication throughout the mobility of User Equipment (UE) is one key challenges facing practical implementation Fifth Generation (5G) networks beyond. One main issues use suboptimal Handover Control Parameters (HCPs) settings, which are configured manually or generated automatically by certain self-optimization functions. This issue becomes more critical with massive deployment small base stations connected mobile users. will essentially require an...

The massive growth of mobile users will spread to significant numbers small cells for the Fifth Generation (5G) network, which overlap fourth generation (4G) network. A tremendous increase in handover (HO) scenarios and HO rates occur. Ensuring stable reliable connection through mobility user equipment (UE) become a major problem future networks. This be magnified with use suboptimal control parameter (HCP) settings, can configured manually or automatically. Therefore, aim this study is...

Recently, home automation system has getting significant attention because of the fast and advanced technology, making daily living more convenient. Almost everything been digitalized automated. The development will become easier popular use Internet Things (IoT). This paper described various interconnection systems actuators, sensors to enable multiple implementations. is known as HAS (Home system). It operates by connecting robust Application Programming Interface (API), which key a...

Various studies have been conducted on the topic of predicting thermal conductivity nanofluids. Here, nanofluids is determined using artificial neural networks since this approach rapid and accurate, as well cost-effective. To forecast magnetohydrodynamic Williamson flow through a vertical sheet, feed-forward network with various numbers neurons has evaluated, best based performance selected. The fluid model incorporates effects Joule heating, heat generation absorption, radiation, chemical...

Abstract Retraction: [Muhammad Shafiq, Fatemah H. Alghamedy, Nasir Jamal, Tahir Kamal, Yousef Ibrahim Daradkeh, Mohammad Shabaz, Scientific programming using optimized machine learning techniques for software fault prediction to improve quality, IET Software 2023 ( https://doi.org/10.1049/sfw2.12091 )]. The above article from , published online on 6 January in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor‐in‐Chief, Hana Chockler,...

Enhanced mobile broadband is an essential target in fifth-generation (5G) networks with higher demands among service consumers. It offers very high-speed Internet connections for several geographical areas: urban, suburban, and rural. Many network operators (MNOs) continuously monitor the quality of terms multiple services to guarantee high performance. To best our knowledge, no extensive studies analyses are conducted on (MBB) that cover various implementation scenarios performance metrics....

The article proposes a new classification method based on implementing the high-speed search tools for indexed data structure created etalon set of features, which has significant advantages in processing speed compared to traditional approaches. classifier is represented as two-stage processing, where at first stage class separate object descriptor determined, and second stage, resulting determined obtained local solutions. developed preliminary construction hash structures descriptors base...

In the published article [...]

In the context of Industry 4.0, improving energy efficiency in smart factories has emerged as a key priority to drive sustainable industrial growth. However, identifying optimal energy-saving solutions is challenging due inherent uncertainty and complexity decision-making. This study addresses these challenges by proposing multi-criteria decision-making (MCDM) framework that leverages intuitionistic fuzzy sets (IFSs) manage ambiguity evaluation process. To advance this framework, we develop...