Exploring nonlinear chaotic systems with applications in stochastic processes.

This manuscript explores the stability theory of several stochastic/random models. It delves into analyzing the stability of equilibrium states in systems influenced by standard Brownian motion and exhibit random variable coefficients. By constructing appropriate Lyapunov functions, various types of stability are identified, each associated with distinct stability conditions.

Enhancing software defect prediction: a framework with improved feature selection and ensemble machine learning.

Effective software defect prediction is a crucial aspect of software quality assurance, enabling the identification of defective modules before the testing phase. This study aims to propose a comprehensive five-stage framework for software defect prediction, addressing the current challenges in the field. The first stage involves selecting a cleaned version of NASA's defect datasets, including CM1, JM1, MC2, MW1, PC1, PC3, and PC4, ensuring the data's integrity.

IoT-based automated system for water-related disease prediction.

Having access to potable water is a fundamental right to well-being. Despite this, 3.4 million people die from diseases caused by water each year, and 1.

Improving crop production using an agro-deep learning framework in precision agriculture.

Background: The study focuses on enhancing the effectiveness of precision agriculture through the application of deep learning technologies. Precision agriculture, which aims to optimize farming practices by monitoring and adjusting various factors influencing crop growth, can greatly benefit from artificial intelligence (AI) methods like deep learning. The Agro Deep Learning Framework (ADLF) was developed to tackle critical issues in crop cultivation by processing vast datasets.

Adherence to Self-Monitoring of Blood Glucose and Its Related Factors Among Type 2 Diabetic Patients Attending Al-Ahsa Primary Health Care Centers in Saudi Arabia.

Background: Self-monitoring of blood glucose (SMBG) is a crucial component of diabetes management, but adherence remains suboptimal. This study aimed to evaluate adherence to SMBG among type 2 diabetic patients in Al-Ahsa, Saudi Arabia.

Methods: A cross-sectional study was conducted among 398 type 2 diabetic patients attending primary healthcare centers.