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The incorporation of energy from renewable sources into the power grid is crucial for achieving sustainable and environmentally friendly power generation. This study proposes an artificial intelligence (AI)-enabled methodology for the analysis & optimization of “grid-tied solar photovoltaic (PV)-fuel cell hybrid power systems.” The research aims to demonstrate how AI techniques can assist in decision-making, improve system performance, and achieve higher levels of energy efficiency and financial viability. The study presents the results of a project focusing on a renewable energy system that feeds into the grid and powers a university building. The hybrid power system’s performance and cost were evaluated using unified approaches to modeling, simulation, optimization, and control. The findings indicate that the AI-optimized “solar PV-fuel cell hybrid system connected to the grid” offers excellent performance, meeting 74% of the building’s energy needs through renewable sources. The system also achieved a low levelled price for energy and minimise CO2 emissions, further enhancing its environmental sustainability. The proposed AI-enabled approach proves to be a promising solution for creating grid-connected renewable energy systems with significant benefits for energy efficiency, cost-effectiveness, and environmental impact.

This research offers a comprehensive examination of the most effective approach to synchronize overcurrent relays within a protective system alongside protective relay. Every effort has been made to encompass all potential strategies for achieving optimal coordination among overcurrent relays. Both modern approaches, like Harris hawk optimisation, and more traditional ones, such ground-based circuit breakers, are included in this category of overcurrent protection with Electric Vehicle. The operation of a Smart Grid [1] is characterized by varying load demands, generation levels from DGs, and charging/discharging behaviours of EVs. These factors can lead to different fault currents and altered fault impedance profiles at various times. An adaptive coordination scheme can dynamically adjust relay settings based on these changing conditions to optimize sensitivity and minimize coordination time. In this paper briefly discuss traditional approaches but focus mostly on using Harris Hawk Optimisation to enhance the coordination of overcurrent relays. This document compiles citations for all relevant works and offers a concise overview of the study conducted. Furthermore, the outcomes of these methods are documented in their corresponding references.

Healthcare fraud is the deliberate misrepresentation of the healthcare industry for the purpose of obtaining unjustified financial gain. There are many different types of healthcare fraud, which can influence patients, healthcare professionals, insurers, and government programmes, such as Billing Fraud, Kickbacks and Bribes, Prescription Fraud, False Claims, Provider Licensing Fraud etc...Healthcare insurance fraud is a severe problem that has an impact on everyone's access to affordable healthcare. Topic modelling can play a role in addressing healthcare insurance fraud by assisting in the detection, analysis, and prevention of fraudulent activities. Overall, the public benefits from healthcare insurance fraud detection because it supports equitable, open, and effective healthcare systems.

Forest fires have become a major threat these days. The hazard posed by forest fires has increased globally. It has a detrimental effect on both human and forest ecosystems. Forest fires can be due to natural changes such as changes in the climate and the Greenhouse effect is due to human activities. Human activities are the major reason for forest fires interestingly. It is important to spot the fires early to reduce the major destruction and loss. In this project, we have proposed a system and methodology which is a wireless sensor network to identify forest fires in early stage. Our project will help to detect the fire in the early stage by using the sensor and intimate through a buzzer and a message to the administration of the forest, therefore the immediate necessary actions can be taken in time and can stop the fire. Administrative officers are constantly monitored. This system has many benefits and protects the environment, forest survivors, infrastructure, lives, and ecosystem. Saving our environment is a major thing in this developing country and world. Forest fire is a biggest natural and man-made calamity int he world. It’s a environment tragedy. Once the fire is not detected and it spreads over a huge area destroying everything, such destruction should be avoided and should save our forest habitats effort of this project is to create and implement a IoT based system that can sense and detect forest fires in early and notify to the responsible officials.

In this project, the creation and application of computer-based fault detection methods for transmission lines with multiple terminals are discussed.These methods are part of a fault-finding system that precisely locates the fault site by using voltage and current signal measurements from smart electronic devices installed on transmission-line terminals. The transformer loading, connection type, and electrical characteristics are all data that the algorithms have access to. The power system components used by the fault-location techniques are likewise presented in this project’s phase component models.

This research centers on optimizing the machining process of Al7072 alloy reinforced with carbon nanoparticles. While surface roughness is the primary research focus, it is one of the most critical parameters in the manufacturing of aerospace components. According to the Taguchi design of experiments tool, the structured experimental framework has been used to learn the precise consequences of Cutting speed (Cs) , Feed rate (Fr), and Depth of Cut (DoC) on surface roughness outcomes. Using cutting-edge algorithms, particularly the Artificial Neural Network, significantly increases these predictive abilities. It hence forecasts the surface roughness achieved with various machining outcomes. According to the initial results, the surface roughness response is extremely dependent on the machining outcomes. The signal-to-noise ratio conducted the statistical analysis to discover the best parameter equation that would allow for the best surface quality and machining economy. Furthermore, the ANN-based model has been created, demonstrating a high level of accuracy in providing feed response. This might be used to optimize the machining process. The results recommend improving the accessibility of machining and increasing aerospace equipment’s quality of service. Thus, the process presented in this research might improve the public’s communication with respect to machining and machining economics.

Concrete ductility and other technical qualities, such as toughness and load-bearing capacity after cracking, are known to benefit from the presence of different kinds of fibres. Recent years have seen a rise in the application of polypropylene fiber-reinforced concrete (PFRC) to a variety of structural elements. The incorporation of polypropylene fibres into concrete to increase the load-bearing capacity of existing structural elements has garnered significant attention. A technique known as "cement-base bonded overlay" has been used recently to increase the flexural capacity of concrete slabs by covering an existing slab with a light covering of PFRC. The aim of this study is to examine the flexural behaviour of a precast concrete slab that has a concrete topping made of Polypropylene fibre (PF). Experiments revealed that the addition of polypropylene fibres to the topping influenced the flexural performance. Despite this, the results indicated that the PFRC covers slab's ductility factor and deflection were better than those of a regular concrete topping slab.

The entire world is facing a water crisis due to population growth as well as global warming. The maximum quantity of water is utilized for industrial and agricultural purposes. Based on these causes, each nation focuses on wastewater recycling techniques. Researchers have innovated a myriad of wastewater treatment methods, along with natural and artificial methods. Apart from this, cost plays a major role in the massive waste water treatment process. By considering the factor generally, the water treatment projects effectively concentrated on assigning natural and easily available materials. This research focuses on industrial wastewater treatment. A water purification process is meant to remove or reduce contaminants in water until it is safe to use. In addition to increasing the odour and flavour of the water, the purification procedures used in this experiment will help to eliminate pollutants and give it a cleaner appearance. This procedure employs natural membranes such as coconut coir, charcoal, and fine sand. This strategy is simple and preferred by anyone owing to the low cost and local availability of the required supplies. On observing the experimental test results, the natural membrane materials provide an effective performance change in the properties of waste water within acceptable limits.

The increasing propagation in recent years of hatred on social media and the dire requirement for counter measures have drawn critical speculation from state run administrations, organizations, and analysts. Despite the fact that specialists have observed that disdain is an issue across different Social media stages, there is an absence of models for online disdain location utilizing this multi-stage information. Different techniques have been produced for robotizing disdain discovery on the web. Here we will begin by giving the current issue that comes the right to speak freely of discourse on the Internet and the abuse of virtual entertainment stages like Twitter, as well as distinguishing the holes present in the current works. At long last, figured out how to tackle these issues. It is a considerably more testing task, as examination of the language in the common datasets shows that disdain needs one of a kind, discriminative highlights and in this manner making it challenging to find. Removing a few exceptional and significant elements and joining them in various sets to look at and dissect the presentation of different machine learning classification calculations as to each list of capabilities. At long last, subsequent to leading a top to bottom investigation, results show that it is feasible to fundamentally expand the classification score acquired.

The present study aims to evaluate the probiotic potential characters isolated from palm wine and different fermented foods. The strains isolated from palm wine and sourdough were Lactobacillus fermentum and from cucumber was Pediococcus acidilactici which exhibited potential probiotic characters when tested in vivo. L. fermentum isolated from palm wine exhibited equal tolerance with strains isolated from sourdough and cucumber. Results presented in this study revealed that L. fermentum from palm wine could withstand the harsh conditions in the gastro-intestinal tract by tolerating the low pH, bile salts, 0.5 % pancreatin and 0.2 % phenol in vitro conditions. The potential probiotic characters exhibited by L. fermentum can be further investigated in vivo and in vitro studies to elucidate the health benefits and assess technological performance as novel starters. Along with sourdough and fermented cucumber, palm wine was a good source for the isolation of prominent probiotic strains for the application at industry level.

Wire electric discharge machining (WEDM) is one amongst the unconventional machining processes which might cut all kinds of shapes with an accuracy of +/−0.001mm. It will cut the materials that conduct electricity and can even cut the exotic metals like tungsten carbide, Hastelloy, Inconel etc. In the present work, machining on Inconel 600 by wire EDM with cryogenically treated brass wire is performed. Brass wire of 0.25mm diameter has been cryogenically treated at −90°C, −100°C and −110°C temperatures separately. An Experimental layout is designed as per Taguchi’s L-9 orthogonal array and experiments were conducted by varying machining parameters viz. Voltage, Pulse ON time and Pulse OFF time. The machining parameters are optimized using Taguchi’s methodology for minimum surface roughness and maximum metal removal rate (MRR). A Mathematical regression model for surface roughness and MRR is generated with the help of regression analysis. Through the Analysis of Variance (ANOVA) It was found that for MRR, pulse on time is the foremost contributing factor with 32.69% and for surface roughness, pulse off time is the foremost contributing factor with 23.59%.

The growth of the industrial sector has resulted in a higher use of Aluminium Metal Matrix Composites (AMMCs). These composites are well-known for their exceptional mechanical and tribological qualities, attracting worldwide attention, especially in the automotive, architectural, and aerospace industries. Advanced Metal Matrix Composites (AMMCs) exhibit increased specific strength, improved strength-to-weight ratio at increasing temperatures, and better wear resistance when compared to the basic matrix without any additional components. SiC and B4C particle reinforcements are used to enhance the metallurgical and mechanical characteristics of the base matrix. Authors have used several production methods such as Powder Metallurgy for solid-state procedures and Stir Casting, Compo-casting, Squeeze Casting, and in-situ casting for liquid-state processes to create AMMCs. Stir casting is the most cost-effective and easy process for producing AMMC. This article provides an in-depth explanation of the procedure for producing Aluminium Matrix Metal Composites (AMMCs) utilising AL-7175 as the matrix material, together with B4C and SiC as reinforcements, with the stir casting technique.

Wireless Sensor Networks (WSNs) play a vital role in achieving quick and efficient results. These networks comprise small, affordable sensors that collect valuable data from their surroundings. The core objective of this project is to optimize the pathways for data transmission, improve communication among sensor nodes, and filter out irrelevant or erroneous data prior to sending it to the central station. This project introduces a new method by implementing blockchain intelligence, which stores and provides optimal data transmission routes. This empowers sensor nodes to identify the most efficient paths for data sharing, eliminating unnecessary routes. Additionally, the blockchain acts as a filter, ensuring that only relevant data is transmitted to the central station. This approach not only saves time by streamlining data routes but also secures data security through the validity of blockchain technology. Furthermore, increases data quality by discarding unnecessary information. This project showcases a smart solution that tackles common WSN challenges, promising to elevate technological capabilities for a variety of applications.

To investigate the stability of the earth embankments and slope failures during natural disasters, it is necessary to consider that soil is naturally unsaturated. Hence, it is essential to understand the variations of pore air pressure and pore water pressure, in terms of suction. The relationship between soil suction and soil moisture content is generally attained by soil water characteristic curve (SWCC), which is critically important in characterizing the mechanical behaviour of unsaturated soils. The SWCC is obtained from pressure plate apparatus by imposing the suction continuously by draining water from the saturated specimen and/or supplying water to unsaturated soil, which differs from the actual soil compaction process at the site. Therefore, the current study employs a methodology of suction measurement directly at a certain degree of compaction and degree of saturation using the membrane filter method in the triaxial apparatus, to meet the realistic conditions in the field. A comparative study has been done using SWCC with the imposed suction and the measured suction (Natural suction) at each compacted state. The results from both the methods exhibited an increase in the suction and air entry value with the increase in the degree of compaction, proving that an increasingly positive effect of suction contributed while increasing the density. Whereas the suction measured immediately after the compaction (Natural suction) in triaxial apparatus is more consistent with the suction imposed in the wetting process of SWCC. Further deep understanding of the microstructure behaviour of each compacted state and the SWCC is necessary.