Volume 12 | Issue 5 |

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Scientific Attitude, Secondary School Students.

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Creative Commons Attribution 4.0 and The Open Definition

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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

KEYWORDS: Linear regression, price Detection System, Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

 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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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Air pollution is the presence of human-harming substances in the atmosphere. It is linked to a significant risk of cardiovascular diseases (such as strokes and ischemic heart disease), chronic obstructive pulmonary disease, asthma, lower respiratory infections, and lung cancer that cause premature death. The primary gaseous pollutants are volatile organic compounds (VOCs), such as polycyclic aromatic hydrocarbons (PAHs), as well as inorganic substances like lead or chromium (Pb or Cr), ozone (O3), carbon monoxide (CO), sulphur dioxide (SO2), nitrogen dioxide (NO2), and carbon dioxide (CO2). The respiratory symptoms of asthma, which include coughing, wheezing, dyspnoea, and chest tightness linked to fluctuating expiratory airflow limitation, are indicative of a chronic inflammatory airway disease. tiny particles in the air that are present in smoke, haze. As a result of breathing in tiny particles from contaminated air, soot and airborne dust can cause major issues with air quality and irritate your lungs. Inhaled tiny particles and irritating gases can pose a larger risk to individuals suffering from asthma. They may aggravate asthma by irritating the respiratory tract. Although anybody can be affected by air pollution, those who have asthma are more vulnerable. Pollution both indoors and outside can aggravate asthma symptoms.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

asthma conditions, air pollution, outdoor air pollutants, indoor air pollutants, asthma symptoms, exacerbations, management

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: Online courses play an significant role in the developing of new skills in students. As a result of open learning platforms and online courses, there is an increasing number of online courses, and certifications available on the internet from various universities. This project is a machine learning-driven course recommendation system that uses the concepts of decision trees in machine learning to provide an effective method for making decisions and generating all the possible outcomes. The K-NN algorithm also helps to store all the available data, classifies a new data point based on the similarity, and produces the desired results. This project suggests appropriate learning courses for students by viewing their study streams and interests. For students to achieve their ideal goals, choosing a learning pathway is essential. However, since there is an abundance of knowledge that is obviously related, it can be difficult for students to select a course that combines their interests and future demands. This proposed framework suggests courses that have previously been taken by similar students, facilitating students to choose a course of study based on their interests. The suggested method makes use of a number of data mining strategies to find correlations between courses. Evaluations based on analysis parts are a key component of the project's methodology. With the help of these methods, we are able to select a suitable course that is given as input, then provide courses that satisfy various requirements. The outcomes meet the requirements for discovering related courses and providing them via cross-platform apps to the students who will use them to enhance their education.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Collaborative Filtering, Decision Tree (DT), K-Nearest Neighbor (KNN), Linear Regression

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Creative Commons Attribution 4.0 and The Open Definition