Applied Science and Engineering Journal for Advanced Research

Design of a Trajectory Tracking Controller for Coreless Tubular Linear Motor Using Model Predictive Controller

Nguyen Trung Thanh — 2025-03-29

This paper presents a cascaded control structure for a coreless tubular linear motor. The system includes position and speed loops employing PI controllers, and a current loop using Finite Control Set Model Predictive Control (FCS-MPC). This structure addresses challenges associated with low stator inductance, specifically its impact on current control. A simulation model was developed using MATLAB/Simulink. The simulation results demonstrate the effectiveness of the proposed solution in tracking the desired trajectory and minimizing the negative effects of low stator inductance on the current loop.

Alkali Interaction with Expansive and Non Expansive Soils

Neethu John — 2025-03-29

This research examines the interaction of alkali contaminants with both expansive and non-expansive soils, specifically black cotton soil and red soil, while assessing the effectiveness of sulphur and gypsum in restoring soil pH for geotechnical stability. Alkaline contamination, commonly caused by industrial effluents, construction activities, and agricultural practices, alters soil behavior by influencing its strength, swelling-shrinkage properties, and overall suitability for construction and infrastructure development. Laboratory experiments are conducted to evaluate the impact of alkalinity on key soil properties, including Atterberg limits, swelling potential, shear strength, permeability, and consolidation characteristics.

Expansive soils, such as black cotton soil, exhibit significant volume changes with moisture fluctuations, whereas non-expansive soils like red soil respond differently to alkali exposure. The presence of alkali contaminants can lead to reduced cohesion, increased dispersibility, and diminished bearing capacity, which pose risks to foundations, pavements, and embankments. This study investigates the potential of sulphur and gypsum as chemical stabilizers to counteract the negative effects of alkalinity. Controlled soil treatment trials are conducted to systematically assess variations in soil pH, structural integrity, and overall engineering performance.

The results offer valuable insights into the geotechnical consequences of alkaline contamination and the effectiveness of remediation techniques in stabilizing affected soils. By addressing the challenges posed by contaminated soils in civil engineering applications, this research contributes to sustainable ground improvement strategies, enhancing the durability and safety of infrastructure projects in impacted areas.

Gesture Control Revolution: Enhancing Automotive Infotainment through Advanced Hand Gesture Recognition

Ravindra Vijay Eshi — 2025-03-29

In the ever-developing industry of automobiles, a focus should be made on the innovation of the car’s user experience while keeping the driver safe. The following paper therefore aims at proposing a new hand gesture recognition system to be implemented in car infotainment, which employs a modified CNN model enhanced with KNN for enhanced gesture mapping. The efficiency of the system was tested on a data of samples consisting of 10000 images of 10 different gestures performed by different users under different lighting conditions. The results obtained for the experimental evaluation proved that the used CNN reached the accuracy of 92,5% with the validation set and the further use of KNN for post-processing increased the classification accuracy up to 95,2%. Resource consumption was low, the CNN occupied roughly 50 MB of memory, that is why it is possible to use it for the in-vehicle system. A similar survey that targeted users showed that 85% of them were comfortable with the system as it was easy to learn and did not interfere with the control of infotainment functions. This research discusses the possibility of using gesture recognition technology to improve the user experience in vehicles making infotainment systems safer and more efficient.

Leveraging Microservices and Serverless Architectures for Enhanced Enterprise Agility

Rahul Ranjan — 2025-03-29

This study investigates the impact of serverless and microservice architectures on the agility, scalability, and cost efficiency of an enterprise. Modern digital enterprises can no longer rely on traditional monolithic architectures due to constraints on deployment velocity, flexibility, and scalability. The research underlines the far-reaching benefits of microservices in modularity, resource consumption, and development cycle time optimization, while also noting the benefits of serverless computing in infrastructure expenditure, auto-scaling capabilities, and performance enhancement. Moreover, the integration of services was analyzed with a focus on security hygiene through policy enforcement, authentication, and workload distribution techniques. It is indisputable that the shift towards microservices and serverless structures provides enterprises with the ability to rapidly achieve innovations, operational agility, and scalability. This study has proven that the adoption of cloud-native architectures is imperative for enterprise modernization and attaining competitiveness within the ever-evolving realm of information technologies.

Forecasting Performance: Leveraging Machine Learning on Earned Value Data for Proactive Control

Rohit Shinde — 2025-03-29

This study investigates the utilisation of machine learning methodologies in the context of earned value management (EVM) data, aiming for the anticipatory prediction and regulation of project outcomes. This research seeks to utilise machine learning frameworks, including regression analysis, decision trees, and neural networks, to forecast upcoming project outcomes, pinpoint possible risks, and improve the decision-making process. The study illustrates how the incorporation of sophisticated algorithms alongside conventional EVM data can yield enhanced, immediate insights into cost and schedule effectiveness. The document further explores the ramifications of this methodology for project leaders, providing a comprehensive structure for enhancing project oversight and regulation via insights derived from data.