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

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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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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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Scientific Attitude, Secondary School Students.

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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: 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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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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U-Net, LeNet , Classification

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

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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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 Keywords

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

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 Abstract

E-commerce as anything that involves an online transaction. E-commerce provides multiple benefits to the consumers in form of availability of goods at lower cost, wider choice and saves time. The general category of ecommerce can be broken down into two parts: E-merchandise and E-finance. E commerce involves conducting business using modern communication instruments: telephone, fax, e-payment, money transfer systems, e-data interchange and the Internet. Online businesses like financial services, travel, entertainment, and groceries are all likely to grow. Forces influencing the distribution of global e-commerce and its forms include economic factors, political factors, cultural factors and supranational institutions.

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E- commerce, modern communication, GST.

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This report examines the impact of technological advancements on retail sales in the mutual fund industry, focusing on how digital platforms, mobile applications, and automated investment tools have transformed the landscape. It explores the benefits, such as increased accessibility and convenience, alongside the challenges, including security concerns and complexity. The study analyzes customer engagement, identifying the most promising technological features, and addresses the varied effects of the COVID-19 pandemic on technology adoption in mutual fund sales. The report offers recommendations to enhance user-friendly interfaces, strengthen security measures, provide personalized financial advice, and leverage social media for investor engagement. These insights aim to guide mutual fund providers in optimizing their strategies for a technology-driven retail sales environment.

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 Keywords

Mutual Funds, Retail sales, Technology, Asset Management Companies

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Abstract: This study explores the impact of neighbourhood contextual factors on alcohol use and related issues in Wayanad, Kerala, India with a notable prevalence of alcohol-related problems, particularly among the Scheduled Tribes (STs), constituting 18% of the population. Recognizing the diverse negative consequences associated with alcohol use, including health, social, economic, and psychological problems, alongside discrimination and stigma, this research employs a mixed-methods approach. Quantitative data collected from respondents Qualitative insights were gleaned from 60 purposively selected respondents through semi-structured interviews, exploring their experiences with alcohol use and problems, and the influence of contextual factors. Findings reveal higher rates of alcohol use and issues among STs compared to non-STs, varying significantly across villages. The study underscores the impact of neighbourhood contextual factors - poverty, low literacy, diminished social capital, and increased alcohol availability - on alcohol use and problems, independent of individual socio-demographics. Qualitative data corroborate and elucidate the underlying mechanisms. The study concludes that interventions should address both individual and neighbourhood factors to tackle alcohol-related challenges effectively. Additionally, it advocates for mixed-methods research to comprehensively understand these issues, suggesting spatial analysis as a valuable tool for identifying and addressing alcohol hot spots. Ultimately, the study contributes to the alcohol-related literature in India, offering valuable insights for policymakers, practitioners, and researchers in addressing alcohol dependence and discrimination in Wayanad.

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alcohol use, neighbourhood contextual factors, alcohol problems, Scheduled Tribes.

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One of the main legislations of law supporting India's efforts to stop illegal financial transactions is the Prevention of Money Laundering Act. Sections 24 and 45, two crucial clauses, have drawn a lot of attention because of their implications for procedural justice and the efficacy of regulations. In-depth analysis of the constitutionality, practical implications, and conformity to international norms of Sections 24 and 45 of the PMLA are done in this research paper. The paper assesses the judicial interpretations, practical ramifications, and evolution of jurisprudence of these rules using an interdisciplinary lens that includes legal, business, and regulatory viewpoints. The study provides insights into the complex interactions between evidential burdens, bail terms, and the overriding goals of preventing money laundering while preserving individual rights and financial integrity. It does this by drawing on landmark case law, legislative changes, and academic discourse. This research contributes to a greater knowledge of the regulatory landscape and enriches ongoing discussions about the effectiveness and equity of anti-money laundering measures in India by clarifying the intricacies and ramifications of Sections 24 and 45.

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PMLA, ED, CA, SC

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The Employees' State Insurance Corporation (ESIC) in India plays a vital role in providing social security and healthcare benefits to workers across various sectors. This research paper aims to delve into the mechanisms of ESIC, exploring recent developments and achievements. Through a comprehensive review of literature, policy analysis, and empirical data, this paper seeks to elucidate the functioning, challenges, and outcomes of ESIC in India. It examines the evolution of ESIC, its organizational structure, funding mechanisms, coverage, and benefits provided to insured persons. Additionally, it assesses recent reforms, technological advancements, and innovations introduced to enhance the efficiency and effectiveness of ESIC. The paper also highlights key achievements and success stories, along with the persisting challenges and areas needing improvement. Overall, this paper contributes to a better understanding of ESIC's role in social protection and healthcare delivery in India.

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Employees' State Insurance Corporation, social security, healthcare benefits, mechanisms, recent developments, achievements.

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Blockchain technology, which offers a decentralized and safe platform for the creation, ownership, and exchange of distinctive digital assets, has emerged as a key component in the growth of Non-Fungible tokens (NFT) markets. NFTs use the immutable ledger of blockchain technology to indicate ownership or authenticity of digital content and to prohibit unauthorized changes. Smart contracts are used by the blockchain technology used in NFT marketplaces, which is frequently based on Ethereum or other compatible blockchains, to automate the generation and execution of NFT transactions. By defining the guidelines for the creation, transfer, and verification of NFTs, these smart contracts do away with the need for middlemen and increase participant trust. The provenance of NFTs is determined in large part by the key aspects of blockchain technology, including decentralization, cryptographic security, and consensus procedures. This addresses issues with intellectual property and authenticity by guaranteeing that the history of any digital item, from its creation to its current owner, is traceable and verifiable.

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NFTs, smart contract, decentralization, blockchain technology.

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This research paper delves into the intricate landscape of horror genres within contemporary fiction, analyzing their evolution, themes, and societal impact. It examines how horror literature has adapted to cultural shifts and technological advancements, influencing and reflecting societal fears and anxieties. Through an exploration of key works and critical analysis, this paper seeks to elucidate the enduring relevance and significance of horror genres in shaping contemporary literary landscapes.

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Horror literature, societal impact, contemporary fiction

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Vehicle to Vehicle communication is one of the upcoming prominent technologies, which aims to provide more road safety measures by providing the important data and information of the vehicles. By introducing Li-Fi technology in the V2V communication enhances the overall performance of the system. The Li-Fi technology helps the V2V communication system to transmit data through a wireless medium at a higher data rate. In Li-Fi, signal is transmitted from a LED and the data is received by the photodetector. In this project, a prototype V2V communication Li-Fi system is designed to avoid road accidents and traffic congestion. The transmitter of the proposed system consists of Li-Fi transmitter module to convert the input data into modulated light signal. The receiver of the proposed system consists of Li-Fi receiver module which decodes the modulated light signal. The decode data is displayed in the LCD. The data shared between two vehicles are speed, temperature and steering angle. These parameters are important to avoid major accidents. Li-Fi technology is used over other transmission techniques, because it is suitable for real time applications.

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Li-Fi, V2V, Speed, Temperature, Arduino, Light, Transmitter, Receiver

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