Department of Mechanical Engineering, Vidya Vikas Institute of Engineering & Technology, Mysuru -570028, Karnataka, India, Sandeep. B., Dr. Shamala N.
et al.
Artificial Intelligence (AI) is transforming healthcare by boosting clinical effectiveness, and operational efficiency. This review highlights AI’s impact on clinical decision-making, precision medicine, and administrative workflows, while addressing challenges like data privacy, algorithmic unfairness, and regulatory hurdles. It also discusses future prospects, including AI-driven personalized treatments and its potential to reduce global healthcare disparities. The paper offers a balanced understanding of AI’s recent applications, challenges, & ethical considerations, offering insight into the obstacles to realizing its full potential in healthcare. Keywords: Artificial Intelligence, Healthcare Transformation, Diagnostic Accuracy Algorithmic Bias, Personalized Medicine.
Assistant Professor, Department of Electrical and Electronics Engineering, Marian Engineering College, Kazhakuttom, Trivandrum. (Kerala), India., Prof. Geena S, Dr. P. Sreejaya
et al.
This paper provides a novel view of using the UPQC (Unified Quality Power Flow Controller) for voltage sag mitigation using Fruit Fly optimization (FFO) control component designed to compensate Real and Reactive Power for a hybrid system and discuss improved hybrid stability. Detailed analysis of the small-line signal of the hybrid model PV-Wind-battery model is considered for different loading conditions. The FFO algorithm is used to provide excellent performance for varying duty cycles. The simulation results show that UPQC has the ability to improve transmission capabilities and is very useful to use. The voltage is compensated 90% using the UPQC-based FFO algorithm. The proposed system also provides a minimum amount of complete harmonic distortion. The simulation results based on MATLAB / Simulink are supported to support the improved concept.
Assistant Professor, Department of Electronics and Communication Engineering, Cheran College of Engineering, Karur, Tamilnadu, India, Kannadhasan S., Dr. Nagarajan R.
et al.
Department of Electrical and Electronics Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India., Sumathi R, Sankari V
et al.
This paper proposes a single phase modified seven level U-Cell inverter configurations in which the advanced process controller has been implemented. By using the boost operation the output of the inverter will produce higher output voltage when compared to the maximum DC source value used. To obtain maximum power the designed inverter is implemented with the photovoltaic system where the power is produced from two different PV panels which is connected to DC link by using DC-DC converters. The semiconductor switches and DC links are used to generate the inverter AC output voltages with seven levels. Two PV panels with different voltages are used in which two panels voltages are combined and their powers are injected to the grid. To validate the dynamic performance of the proposed U-Cell inverter the advanced process controller is used in the inverter connected to the grid. The controller is designed and processed to maintain the capacitor voltage to obtain the desired AC output with desired magnitude. The dynamic performance during changes in the supply current and DC voltage of capacitor for the process controller has been obtained.
UG Student, Department of Electrical and Electronics Engineering, Saveetha School of Engineering, Chennai, India., Vishnupriya K., Ramya G.
et al.
This paper enlightens the analysis of distributed transformer using novel controller. The transformer initiates power distribution by stepping up or down depends upon the need. In accordance with power quality issues, performance, dynamic response, power factor correction the normalized transformer is inconvenient. Replacing the uncertainties by introducing a power electronic distribution transformer (PET) with PI controlled adaptive fuzzy logic control (APIFC). Moreover the occurrence of breakdown voltage and stress in conventional method, this method becoming more popular. This transformer become sensitive to dealt with swell, sag, voltage regulation, open circuit and short circuit fault. The specified rectifier also does power factor correction. The strategic PI controller with adaptive fuzzy logic control technique is established to respond sudden change or variation occurs in load. The fuzzy logic controller (FLC) posses five set of rules and PI controller adapt with one among five set of rules. This makes the controller to adjust with variation and improves power quality. The simulation is carried out using MatLab-Simulink.
Department of Electrical and Electronics Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, India., J. Janapriya*, M. Rathaiah
et al.
In this paper, the structure of the P-I controller has been revised to I-P controller structure, for the model of First-order plus time delay and model of Half-order plus time delay. P-I controller is the dominant controller used for most of the Industrial processes. However, high peak overshoot and sensitivity to controller gains are some of the disadvantages faced by P-I controller . The objective of this study is to overcome these disadvantages, I-P controller has been implemented. Simulation results obtained using MATLAB/simulink shows that the I-P controller tuning approach provides enhanced performance and reduction in the peak overshoot when compared with P-I controller tuning.
PG scholar, Department of Electrical and Electronics Engineering, V R Siddhartha Engineering College, Vijayawada, A.P, India, K. Indira, Dr. B. Srinivasa Rao
et al.
In power system studies the most important issue is Transmission Expansion Planning (TEP). The intend of TEP problem is to choose the placement as well as number of additional transmission lines, which are to be added to the existing system to suit growing demand in planning horizon. In this paper a new methodology for TEP is proposed, the presented Transmission planning is linked with generation cost, active power loss minimization by considering wind uncertainties. Firstly, the uncertainties involved in wind generation can be determined by using weigbull probability functions. Monte Carlo simulation study is able to be used to find the probability distribution functions of wind generation. Then, in TEP formulation the WTG uncertainties are considered. Particle swarm optimization (PSO) technique is used for solving the proposed single objective optimization problem. Simulation studies conducted on an IEEE 30 bus test system to certify effectiveness of the TEP problem with considering wind uncertainties.
BABU K. KIRAN, PG Scholar, Department of
Electrical and Electronics Engineering, Sri Vasavi Engineering College,
Andhra Pradesh, India, RAMBABU CH
et al.