Journal of Science Engineering Technology and Management Science

Hydrogen systems have been undertaken in this study. As The study utilizes the yearly energy production of a privately-owned wind power plant in Izmir Cesme as a reference. Calculations are based on the facility's annual electrical power curves and the potential hydrogen and electrical power output. The hydrogen power plant operated at approximately 50% load factor, resulting in a hydrogen cost of 0.043 $/MJ. Graphs illustrate potential electricity costs for various load factors. At a 0.40 load factor, the unit hydrogen cost is 0.98 $/MJ, while at 0.70, it decreases to 0.40 $/MJ. The findings are examined, and visual representations are used to elucidate the impact of enhanced power and load factor of the unit cost of hydrogen.

Keywords : Economic analysis, Hydrogen energy, Wind energy, Renewable, Battery

Author : Srinivasa Varma and Pandian

Title : Hydrogen Production by Wind Power: An Economic Analysis

Volume/Issue : 2025;02(01)

Page No : 01-05

In this paper we consider the complete control of a wind generator system connected to a plant. A control framework based on a four-leg inverter connected to the grid side is formulated to input the supplied power and at the same time act as an active power filter to reduce many disturbances and increase the power quality. The system considered is a four-wire system comprising three phase and single phase straight and nonlinear lot. The utility-side controller compensates for disturbances due to receptive, nonlinear, and out of balance single load(s) and intra phase loads as well as dynamic

Keywords : Inverter controller, triggered generation, grid-connected system, and power quality

Author : T.Hima Bindu

Title : Wind Power Production System Connected To The Grid with External Storage

Volume/Issue : 2025;02(01)

Page No : 06-08

Without power, any component is just a bunch of idle parts. This is especially so with those that rely on the non-renewable sources. We need to make a pro-active shift in our energy source from fossil fuels to renewable source. This paper describes the design of a Solar Powered BLDC Motor Driven Electric Vehicle which is one approach to tackle the upcoming crisis. In this work, the approach chosen for selection of suitable elements in this application is reviewed and each one are modelled simulated and tested through real time environment. The solar module, charge controllers, batteries therefore were integrated to the boost converter and BLDC motor made up the Solar Powered Electric Vehicle henceforth developed.

Keywords : Photovoltaic, renewable energy, solar vehicle, and BLDC motor

Author : Pravallika

Title : BLDC Motor-Driven Electric Vehicle Design: Solar-Powered

Volume/Issue : 2025;02(01)

Page No : 09-14

A polyphase induction motor's starting current is five to eight times its rated current when it is started from rest with full voltage impressed. Such a motor's huge line current is undesirable since it may cause a sudden reduction in the supply circuit's voltage and have an unfavorable effect on other connected loads or devices. Therefore, it is common practice to use auto transformers, star delta starters, and other devices to start such motors at a lower voltage. This work presents a novel technique for starting polyphase induction motors without the need for a primary voltage compensator, which lowers the inrush of the starting current. The motor's appropriately accelerated rotor is then driven in the designated direction of rotation using a crank-driven system. After that, the motor is tested with its rated voltage applied. Through oscillographic recordings obtained from experiments, where the results are contrasted with the various beginning approaches, this is illustrated with a case study on a three-phase, five-horsepower NGEF motor.

Keywords : Starter, inrush current, voltage drop, induction motor, and novel method

Author : Raja Sekhar Reddy and Niharika

Title : A Comparative Analysis of a New Approach to Induction Motor Starting

Volume/Issue : 2025;02(01)

Page No : 15-19

The project's central topic is avoiding human presence, which also functions as an automatic action that accepts payment and allows the car to move or stop. These days, this project is crucial, and we are developing the application by combining RFID technology with GSM. RFID plays a part in identifying the vehicle. The RFID will activate, the reader will read the tag, the microcontroller will check the database, and the balance inquiry will be processed if the vehicle is entered. If there is sufficient money on the card, the gate will open; if not, it will automatically close after two minutes when the automobile passes. If there is no balance on the card, the gate will not open it. This also serves as a GPS to find the car. We are aware that GSM is utilised to determine the precise location of the car. Longitude and latitude (GPS) information are returned by the controller when it receives it. The vehicle system portion uses a high-end 32-bit ARM7 CPU, and the transmission system section uses a PIC microcontroller because of how quickly its instructions are executed.

Keywords : GSM, GPS, 32 Bit Microprocessor, ARM7 Processor, RFID Technology

Author : R.Sasidhar

Title : Design of an Electronic Toll Collection-Based Intelligent Transportation System

Volume/Issue : 2025;02(01)

Page No : 20-24

Parkinson’s Disease (PD) is a chronic and progressive neurodegenerative disorder affecting millions worldwide. Early and accurate diagnosis is critical for effective intervention and management, but the inherent variability and overlapping symptoms with other neurodegenerative diseases make classification a challenging task. Traditional machine learning methods have offered valuable insights but often fall short when dealing with complex, high-dimensional biomedical data. This paper introduces a hybrid classification framework combining attention mechanisms with an ensemble learning approach to enhance the predictive accuracy and robustness of Parkinson’s Disease classification. The proposed method integrates attention-based deep learning for feature selection with ensemble methods such as Random Forest, Gradient Boosting, and Voting Classifiers to improve generalization and interpretability. Attention layers help focus on the most relevant features—such as gait patterns, speech signals, or tremor-related data—while ensemble techniques reduce model variance and bias. We evaluated the system using benchmark datasets, including voice recordings and movement signals, from the UCI Parkinson’s dataset and other publicly available repositories. Experimental results show that the combined approach significantly outperforms traditional single-model baselines in terms of accuracy, precision, recall, and F1-score. This work contributes to the growing field of AI-driven healthcare by demonstrating that attention mechanisms and ensemble models can work synergistically to improve disease classification. Furthermore, the model offers promising potential for real-world clinical applications, especially for early detection and remote monitoring. Our findings provide a compelling case for integrating interpretability, robustness, and automation in medical decision support systems.

Keywords :

Author : T. Surekha, R. SivaRama Prasad

Title : AN ENSEMBLE HYBRID ATTENTION MECHANISM APPROACH FOR PARKINSON DISEASE MULTI LABEL CLASSIFICATION

Volume/Issue : 2025;02(01)

Page No : 25-36