Volume 12 | Issue 5 |

 Abstract

The main aim of this research objective is to find the company's last five years profitability, Asset & Liability position and they are using the ratios to make decision in the complicated periods. the objective of the research is to identify the year to year company financial. position

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 Keywords

Financial performance, Ratio Analysis, Trend percentage,

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Microspheres are spherical particles with diameters typically ranging from tens to hundreds of micrometers, extensively utilized in various fields including pharmaceuticals, biotechnology, and materials science. Among the methods employed for their formulation, solvent evaporation stands out as a versatile and widely adopted technique. This abstract aims to provide a concise overview of the process involved in formulating microspheres via solvent evaporation. The process begins with the dissolution of a polymer or a blend of polymers in a volatile solvent, forming a homogeneous solution. Optionally, an emulsification or dispersion step may follow to encapsulate hydrophilic substances or control release properties. Subsequently, the polymer solution is subjected to controlled evaporation to remove the solvent gradually. As the solvent evaporates, the polymer precipitates, leading to the formation of solid microspheres. Parameters such as polymer choice, solvent selection, and processing conditions are carefully optimized to achieve desired microsphere characteristics. Solvent evaporation offers several advantages including precise control over particle size and morphology, versatility in encapsulating both hydrophobic and hydrophilic substances, and compatibility with various polymers and active ingredients. However, optimization of process parameters is critical to ensure the desired characteristics and performance of the microspheres.

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 Keywords

microspheres, solvent evaporation, pharmaceuticals, biotechnology, materials science, formulation methods, polymer dissolution, volatile solvent, emulsification, dispersion, controlled evaporation, particle size, morphology, encapsulation, hydrophobic substances, hydrophilic substances, polymer choice, solvent selection, processing conditions, optimization, active ingredients, release properties

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In this era's interconnected world, a corporate's ability to handle a crisis can have a major impact on its reputation and subsequent standing in the market, especially for a service-based industry like the aviation sector. This study explores the complex interrelatedness of image engineering and crisis management techniques in the context of the Indian aviation sector. Using a case study approach, this research looks at significant crisis situations that top Indian airlines have encountered along with influence from landmark precedent crises in the world and evaluates how well their crisis management solutions have shaped public opinion and company reputation. The paper offers a theoretical framework that clarifies the relation between corporate communication and crisis management and examines how these two crucial aspects of corporate reputation management interact. It also explores the unique difficulties and weaknesses faced by airlines in the Indian aviation industry, such as safety worries, disruptions to operations, legal problems, and public scrutiny. This paper assesses the crisis management tactics used by major companies in the Indian aviation sector via a thorough examination of real-world case studies. It looks at the stakeholder engagement initiatives, communication strategies, organizational resilience, and transparency practices used by airlines to lessen the negative effects of crises on their reputation and brand image. This paper also investigates how crisis management affects stakeholder trust and company image restoration over the long run in the Indian aviation industry. It looks at how proactive reputation-building programs, CSR projects, and well-planned communication campaigns can help people become resilient and regain public trust after a disaster. Through the integration of incident reports, industry insights, and theoretical frameworks, this study advances our comprehension of the complex interplay between crisis management and image engineering within the Indian aviation sector.

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 Keywords

Airlines, Crisis Management, Corporate Communication, Image Engineering. Indian Aviation Industry

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 Abstract

Sri Aurobindo maintained that poetry in future would divest itself of the outward trapping like meter, rhyme, even the emotional connection of words. The poetic essence or the essences of poetry would leap like a spark from the poem to the reader. The poet declared that the more directly the word reaches and sinks deep into the soul, the greater the poetry. This kind of poetry was termed "overhead poetry" by Aurobindo.

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 Keywords

overhead poetry, absolute ,ascent, soul, visionary

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In recent years, AI and machine learning have revolutionized the field of animation, transforming the way characters move, interact, and emote on screen. This research delves into how these technologies reshape traditional animation processes, from character design to rendering, by automating tasks, enhancing realism, and unlocking new creative possibilities. By examining case studies and industry practices, this paper explores the profound impact of AI on storytelling, production pipelines, and the future of animated entertainment. Ultimately, it highlights the synergistic relationship between human creativity and machine intelligence, paving the way for a new era of animated storytelling. Also, it does not miss the drawbacks of AI in animation which may have proportional impacts on the jobs and businesses of Animators

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 Keywords

Animation, AI, Machine learning, VFX, Animator, Media

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 Abstract

The microgrids are generally a network consisting of small scale generators supplying a small area but they are not entirely isolated but also connected to the national grid in most of the cases. Islanding is an emergency condition where the main grid goes off while the DG is still connected to the system. This causes potential threat to the whole system. The system may collapse if it is not detected fast and remedial action is not taken. This research work tries to do a systematic study of common methods of islanding detection available and draw necessary conclusions.

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 Keywords

ANN, Fuzzy, Islanding, Microgrid, Zone of nondetection, Active, Passive

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The scientific attitude is a mindset that promotes critical thinking, curiosity, and a willingness to question and explore new ideas. A positive scientific attitude is crucial for children's learning, problem-solving, and future interest in science. The aim of the present study is to study the scientific attitude of secondary school students. The present study dealt with to assess the level of scientific attitude of secondary school students and also find out whether there is a significant difference in scientific attitude of secondary school students based on gender, type of school and locality.

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 Keywords

Scientific Attitude, Secondary School Students.

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 Abstract

Since previous years, machine learning has become increasingly important in major fields, normal speech commands, and product recommendations. Rather than this, it offers safer automotive systems and superior customer services. Given that machine learning (ML) is a popular technology across nearly all industries, we are attempting to include ML into our project. The real estate market is one of the most competitive these days in terms of price and volatility. People are searching to get a new house by analyzing market techniques and sticking to their finances. However, the primary drawback of the existing approach is that it determines a home's valuation without making the essential predictions about future market trends, which drives up prices. Thus, the primary goal is to estimate home prices accurately and profitably. Predicting an accurate house price requires taking into account a number of variables, including the customer's preferences and budget, in order to provide effective house pricing. Thus, we are developing a model to forecast housing costs. by utilizing linear regression and other machine learning algorithms.

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KEYWORDS: Linear regression, price Detection System, Machine Learning

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 Abstract

Modern car insurance industries waste a lot of resources due to claim leakages, which determines the amount they pay. Currently,visual Inspections and Validations are done manually,which can delay the claim processes.Previous study have shown that classifying images is possible with a small data set,by transferring and re purposing knowledge from models trained for a different task. Our goal is to build a Car Damage classifier using a deep learning model that is able to detect the different damage types and give an accurate depiction given a car image. However, due to the limiting set of data, it can be result in being a determining factor.Training a Convolutional Network from scratch (with random initialization) is difficult because it is relatively rare to have a large enough dataset.In this project we explore the problem of classifying images containing damaged cars to try and assess the monetary value of the damage. Because of the nature of this problem,classifying this data may prove to be a difficult task since no standardized dataset exists and some of the clases utilized might not be discriminative enough. Utilizing a pretrained YOLOv8 model,we trained a classifier in order to categorize the dataset,testing 3 different cases: damaged or not (damage vs whole),damage location (front vs rear vs side),damage level (minor vs moderate vs severe).

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YOLO model,CNN

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 Abstract

It uses the Unity Neural Encoding Tool (U-Net) and LeNet-5 to present a novel approach to crack-level classification using Artificial Intelligence techniques. For safety reasons, the primary goal of this study is to locate cracks in a variety of structures, including walls, bridges, and infrastructure. A substantial dataset of 10,000 images was used for this project, of which 8,000 were designated for training and 2,000 for testing. With the help of state- of-the-art deep learning and image processing techniques, the model can classify six distinct types of cracks. They are Normal crack, Deep crack, Gap crack, Riss crack, Wall care crack, and No crack. Using cutting-edge architectures makes it easier to improve upon current practices. In addition to improving safety and maintenance procedures in the civil engineering and construction industries, this research advances the field of quality monitoring by providing a trustworthy method for locating and categorizing cracks.

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 Keywords

U-Net, LeNet , Classification

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