American Journal of Applied Science and Technology

Automatic Approximation of The Surface Model of The Final Distillation of Vegetable Oil Miscella

2025-05-08T11:03:31+00:00

The present study investigates the geometric modelling and surface construction process applied to the optimisation of the apparatus used in the final distillation stage of vegetable oil miscella. The surface is conceptualised as the geometric locus of points representing individual miscella particles, allowing for a more precise simulation of phase interactions during distillation. A key feature of the proposed approach is the generation of surfaces based on predefined sets of curves, through which the structure of the miscella flow can be interpreted and analysed. By employing geometric transformations and interpolation functions, the paper proposes a methodological framework for constructing complex technical forms that reflect the dynamic behaviour of miscella particles. The study also introduces a discrete spatial model using basic geometric primitives, such as planes, polynomials, and second-order curves, to approximate the evolving surface during distillation. The results of this modelling approach can significantly enhance control mechanisms and design efficiency in distillation equipment, providing a mathematically grounded basis for engineering improvements.

Regionalization of Nature Conservation in The Fergana Valley

2025-05-08T12:11:07+00:00

The use of natural resources, mitigation of natural and anthropogenic processes, and environmental protection are inherently interrelated components of a unified and integrated system. These processes are most effectively implemented within specific landscapes or groups of landscapes. The nature conservation aspect of this system holds particular significance. This article examines such processes using the example of the Fergana Valley.

Identifying and Mitigating Security Vulnerabilities in Web Applications

2025-05-08T11:44:40+00:00

As web applications continue to play a critical role in modern digital infrastructure, their security has become a major concern. This article explores the most common types of security vulnerabilities in web applications, including SQL injection, cross-site scripting (XSS), cross-site request forgery (CSRF), and broken authentication. It further outlines various techniques for identifying and mitigating these vulnerabilities, such as input validation, secure coding practices, use of security headers, and implementation of secure authentication mechanisms. The paper also emphasizes the importance of adopting a secure software development lifecycle (SSDLC), updating third-party components, and fostering security awareness among developers. By applying a combination of proactive strategies, organizations can effectively reduce risks, protect sensitive data, and maintain the integrity of their web-based services.

Deep Learning-Driven CNN Approach for Accurate Traffic Sign Recognition in Intelligent Transportation Systems

2025-05-01T02:00:03+00:00

Accurate and robust traffic sign detection is crucial for the development of advanced driver-assistance systems (ADAS) and autonomous vehicles. This paper presents a review of recent advancements in intelligent traffic sign identification using Convolutional Neural Networks (CNNs). The article surveys various CNN-based architectures, methodologies, and optimizations employed to address the challenges of traffic sign detection, including variations in illumination, weather conditions, and sign degradation. The performance and limitations of current approaches, along with potential future research directions, are discussed.

Cybersecurity in Financial Technologies: Current Threats, Methods of Protecting User Data, And Ensuring Business Security

2025-05-09T13:26:08+00:00

The first decades of the energy-information era are marked as a period of digital transformation, accompanied by the large-scale digitalization of key sectors. The financial sector stands at the forefront of this global movement. The rapid development and implementation of modern digital financial technologies present great opportunities for business growth and expansion. At the same time, advanced technologies and innovations adopted in the industry are not always fully protected from various threats. This article explores the current cyber threats typical for the fintech sector, methods of protecting users' personal data, and strategies for ensuring business cybersecurity. It analyzes modern cybersecurity tools and best practices. Special attention is paid to the scientific novelty in the application of artificial intelligence and machine learning. The article concludes that a comprehensive approach to cybersecurity is essential as a strategic element in the development of fintech businesses. The purpose of this article is to examine current threats, analyze data protection methods in the fintech sector, and develop recommendations for ensuring business resilience in cyberspace.

Using GIS And Remote Sensing in Assessing the Impact of Drought on Forest Cover Changes Around the Aral Sea

2025-05-08T11:58:53+00:00

The Aral Sea region has experienced significant ecological changes due to prolonged droughts and unsustainable water use, resulting in the degradation of forest ecosystems. This study utilizes Geographic Information Systems (GIS) and remote sensing techniques to analyze the impact of drought on forest cover changes from 2000 to 2024. Using satellite imagery (Landsat and Sentinel-2) and climate indicators such as the Standardized Precipitation Index (SPI), temporal and spatial trends in vegetation health and forest loss were assessed. The findings reveal a strong correlation between increasing drought severity and the decline of forest cover, particularly in the Amu Darya delta and surrounding areas. The study underscores the importance of integrating high-resolution satellite monitoring with adaptive forest management strategies to mitigate the effects of environmental degradation in arid regions.