Journal of Research in Engineering and Computer Sciences

Design and Implementation of a Practical Board for Generating a PWM Signal to Control the Speed and Direction of a DC Motor

Omar Jasim — 2025-05-26

DC motors are highly employed in industrial, automotive, and automation applications because of their dependability and efficiency. Precise control of both motor speed and rotational direction is critical for enhancing performance and functionality [1]. A precisely and energy-efficient method for obtaining this kind of control is PWM-based control signal. [2]. In this research, the design and implementation of a PWM-based control system for a 775 DC motor, utilizing a 555 timer circuit is presented [3]. While direction reversal is accomplished with a toggle switch, the PWM duty cycle varies the motor's speed. A MOSFET driver circuit is used for the efficiency of power switching, and a fly back diode is used to protect the circuit from reverse electromotive force (back-EMF). [3].by expected experimental results of this control system, three main goals want to be achieved. The first is direct correlation between the motor speed and the duty cycle size for the PWM signal. The second one is the reduction of power consumption when employing PWM-based control compared to other methods of control like the direct voltage control. The second is the reduced energy use achieved by using PWM-based control in comparison to other techniques of control such as direct voltage regulation. The last one is dependable directional switching with minimum daily time particularly at higher speeds. Overall, from the expected results a validation that a PWM-based control system is reliable, energy-efficient, and scalable approach for controlling the speed and direction of a DC motor is required to achieve from the proposed system.

Methodological Aspects of the Study of Personality as an Object of Sociological Science

Samuil Vinogradov — 2025-06-07

The article is methodological in nature. Personality is analyzed as a concept of sociological science and as a subject of social relations. The place of this concept in the system of knowledge about society, its difference from other concepts denoting a person is considered. The article shows the relationship of the personality with society as a whole and with separate social groups, due to the needs of this personality. The methodological basis of such a connection is the conditionality of the most significant social relations by the social division of labor, which gives rise to the differentiation of society into diverse social groups. The article deals with the social structure of personality as a reflection in the individual consciousness of the social structure of society. This refers to the essential conditionality of the consciousness of the individual by its position in the system of social relations, belonging to certain social groups (property, professional, demographic, etc.). The complexity of the process of interaction between the individual and society is shown, which is expressed in the fact that the needs are transformed into the interests, motives of behavior and culture of the individual before manifesting themselves in the behavior of this personality.

Soil Quality Prediction and Classification Using Machine Learning Algorithms

Mohd Jameel — 2025-06-16

Soil quality assessment is critical for sustainable agriculture and land management, yet traditional methods lack scalability and efficiency. This study presents a novel Soil Quality Prediction and Classification (SQPC) framework that leverages advanced machine learning, including hybrid ensembles and deep learning models. Using a rich dataset of soil attributes—such as pH, nutrients, and texture—we apply automated feature engineering and dimensionality reduction (PCA, t-SNE) to enhance interpretability. Ensemble models like XGBoost and Stacked Generalization improve prediction accuracy, while a new Spatial-Aware Neural Network (SANN) incorporates geospatial data for localized insights. Our models achieve over 95% classification accuracy, with the SANN improving predictions by up to 10% in sparse data regions. Explainable AI tools (e.g., SHAP, LIME) enhance transparency, making outputs actionable for stakeholders. The framework also integrates transfer learning and adaptive algorithms for robust performance on small and evolving datasets. This research offers a scalable, interpretable approach to soil quality modelling, paving the way for real-time, data-driven decision support in agriculture and environmental policy.

Optimal Sizing and Cost Analysis of a Hybrid Renewable Energy System for Kirkuk City Using HOMER Software

Hussein Al-bayaty — 2025-06-11

This project aims to design a hybrid system that combines various conventional renewable energy sources, including solar power, wind energy, and electricity from diesel generators, using the HOMER (Hybrid Optimization of Multiple Energy Resources) software. This system designed to supply the city of Kirkuk in Iraq with electrical power during hour's outages. Data have been taken for solar and wind energy were obtained from NASA (National Aeronautics and Space Administration) Which is provided by the Homer, and load shedding data for Kirkuk in 2018 year from Power Generation Stations from Baghdad. Several strategies were created, with the best being a hybrid design that includes solar panels, converters, and batteries over a 25 year at a cost of 5 billion dollar.

Design of a Hybrid Intelligent Traffic Signal Control System Using Nearest Neighbor Algorithm and Deep Reinforcement Learning with SUMO Simulator

Elaf Jirjees Dhulkefl — 2025-06-13

In this paper, a new hybrid intelligent traffic signal control system based on K-nearest neighbors (KNN) algorithm and deep reinforcement learning (DRL) is proposed. The system employs KNN to quickly classify traffic states with historical data, and a DQN to iteratively optimize traffic signal policies on the fly. The hybrid mechanism can overcome the drawbacks of single model based systems as it is capable of combining immediate response and long term adaptability. Extensive simulations on different traffic conditions (including peak hours and extraordinary accidents) indicate that the hybrid system performs much better on average than traditional fixed-timing method and single-algorithm system (KNN-only, DRL-only). In contrast to the traditional system, the hybrid model decreased the average waiting time of vehicles by 48 percent, the number of stops by 58 percent, and improved the throughput of vehicles by 57 percent. These enhancements point to better traffic-integrated urban management and insect-ion efficiencies as well as combined enhanced environmental sustainability of the hybrid model.

Control of a 3- axis Mechanical System Using Servo Motors and FPGA Programming Techniques

Zainab Mahmood Khudhur — 2025-06-22

In order to focus on servo motor systems and how to manage them with FPGA devices, a computer installed on a CNC machine to control the CNC machine through the servo motor drivers and PC that must be synchronized together, which requires quick interface tools, which is viewed as one of the significant issues with CNC technology. The use of a computer and an FPGA-based system control will raise the amount of information available on the topic and support research on it. There is communication between the FPGA and the computer. A graphical software runs on the computer to process the data. Both graphical and numerical representations of this data are possible on the computer screen. Statistical analysis might be performed on this data. The chosen FPGA and the computer work together to produce the necessary control signals for the servo motors. The current study uses FPGA to enable flexible and smooth control of the three servo motor axes.