Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

The study aims to build a model that enhances trust-building for public and private banks to compare and determine the significant differences between public and private banks, by testing the impact of governance mechanisms (transparency, accountability, justice, independence, and social responsibility) (Agere, 2000) on trust-building strategies (trust and trust building, people management, work relations, training and development, leadership practices, and communications) (Ngalo, 2011; Stone et al., 2005), to indicate the level of employees’ awareness of the theoretical contents of the two variables and their importance to banking work, with the aim of improving performance. The main question is the role of governance mechanisms

Background: The anterior knee pain is an important chief complaint of the patients with knee osteoarthritis due to patellofemoral pathology. The pain receptors denervation can be achieved by circumferential denervation of the patellar area by a process of electrocautery.

Objectives: The aim of current study is to assess the pain after total knee arthroplasty (TKA) by patelloplastywith and without circumferential denervation via electrocautery at a minimum follow up with 1 year separately for each patient.

Type of the study:Cross- sectional study.

Methods: Thirty five patients,with mean age of about (62.8) years, were enrolled in this pros

In this paper, a cognitive system based on a nonlinear neural controller and intelligent algorithm that will guide an autonomous mobile robot during continuous path-tracking and navigate over solid obstacles with avoidance was proposed. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) Algorithms are used to finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths and finding the reference path equation of the optimal

Samples of the ovary and uterus of local breed cats used to investigate the histological, histometrical and hormonal features. The paraffin embedding technique was used for processing of tissue that stained by hematoxyline and eosin stain, and massons trichrom stain. Ovary of at proestrus or oestrus phases composed of outer cortex that covered by cuboidal germinal epithelium and inner medulla. Tunica albuginea composed of a thin layer of characterized by fusiform stromal cells. The cortex content groups of Oogonial cells, numerous primordial follicles, little primary, secondary and tertiary follicles in addition for 1-2 follicular cysts and mature corpus letium. In pregnant cat the thickness of ovarian cortex was significantly incre

The evolution of cryptography has been crucial to preservation subtle information in the digital age. From early cipher algorithms implemented in earliest societies to recent cryptography methods, cryptography has developed alongside developments in computing field. The growing in cyber threats and the increase of comprehensive digital communications have highlighted the significance of selecting effective and robust cryptographic techniques. This article reviews various cryptography algorithms, containing symmetric key and asymmetric key cryptography, via evaluating them according to security asset, complexity, and execution speed. The main outcomes demonstrate the growing trust on elliptic curve cryptography outstanding its capabi

Explainable Artificial Intelligence (XAI) techniques enable transparency and trust in automated visual inspection systems by making black-box machine learning models understandable. While XAI has been widely applied, prior reviews have not addressed the specific demands of industrial and medical inspection tasks. This paper reviews studies applying XAI techniques to visual inspection across industrial and medical domains. A systematic search was conducted in IEEE Xplore, Scopus, PubMed, arXiv, and Web of Science for studies published between 2014 and 2025, with inclusion criteria requiring the application of XAI in inspection tasks using public or domain-specific datasets. From an initial pool of studies, 75 were included and categorized in