Volume 12 | Issue 4 |

 Abstract

Academic Stress is a pervasive phenomenon experienced by students across educational settings, characterized by the pressures, demands, and challenges inherent in the pursuit of academic goals. This research paper explores the nuanced interplay between Academic Stress and coping strategies, shedding light on the mechanisms through which students navigate the rigours of academia while striving to maintain their well-being and academic performance. The study employed quantitative research where 130 students were chosen randomly from B.Tech and was screened by using The Perceived Stress Scale (PSS) and coping strategy scale by Holahan and Moos. The results indicated that the mean score for Academic Stress was 20.60 (SD = 129), and the mean score for coping strategies was 35.13 (SD = 129). There was a negative correlation between Academic Stress and Coping Strategies. The study also shows that females have higher Copying Strategies than males, the males tend to face higher Academic Stress even because of external factors The study relied on self-reported data, which can be susceptible to bias. The small sample size limits the generalizability of the findings

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 Keywords

Academic stress, Coping Strategies, college students

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Generative Artificial Intelligence (AI), a subset of AI that generates new content such as text, images, and audio, has recently made significant advances, with key developments including Large Language Models (LLMs) such as OpenAI's Generative Pre-trained Transformer (GPT) -3/4, Large Language Model Meta AI (LLaMA), and Pathways Language Mode. These models, trained on large datasets to detect patterns and context inside language, have proven beneficial for difficult jobs for humans, providing efficiency, accuracy, and uniqueness. This research project uses OpenAI's GPT model to provide personalised applications like as document summarization, question answering, and numerical data analysis. Users may submit documents in a variety of formats and obtain a summary, as well as ask questions to extract responses. This function has several uses, ranging from students summarising educational materials to attorneys summarising court data. Users may also run data analysis procedures on CSV files containing numerical data, which is important for summarising financial information. As technology advances, the potential applications of generative AI models grow, influencing industries such as entertainment and healthcare. These models' versatility makes them useful tools for problem solvers in a variety of sectors. The fast development of huge language models and generative AI in recent years has been astonishing, with OpenAI's release of ChatGPT in 2022 pushing these technologies to the forefront. This paper studies the characteristics and applications of big language models, generative AI, and the features of Retrieval Augmented Generation (RAG). A software programme capable of interactive conversations in the context of specific papers is developed and tested, resulting in an application that is equivalent to commercial solutions. This programme can summarise large papers into simple, succinct English and provide accurate answers to proposed queries. Future optimisation efforts can concentrate on reducing reaction time and comparing the utilisation of various language models.

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 Keywords

Generative Artificial Intelligence (AI), Large Language Model (LLM), OpenAI's Generative Pre-trained Transformer (GPT) -3/4, Large Language Model Meta AI (LLaMA), and Pathways Language Mode (PaLM), Retrieval Augmented Generation (RAG)

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The rapid evolution of cryptocurrencies, such as Bitcoin and Dogecoin, has sparked significant interest and investment, highlighting the need for secure, reliable, and user-friendly platforms. This paper provides a thorough review and analysis of the DevOps CryptoVision project, a pioneering initiative aimed at revolutionizing user engagement with cryptocurrencies. In the ever-changing digital asset landscape, CryptoVision serves as a comprehensive cryptocurrency data and information aggregation platform, prioritizing accuracy, security, and user-centric design. It seamlessly integrates real-time data from various sources to offer a holistic view of the cryptocurrency market. The project leverages a robust DevOps Continuous Integration/Continuous Deployment (CI/CD) pipeline to maintain data accuracy, stability, and security, thereby ensuring a user-friendly experience. DevOps CryptoVision represents a forward-thinking effort that bridges the gap between cryptocurrency markets and users, offering the knowledge, resources, and tools necessary to navigate this dynamic landscape with confidence.

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 Keywords

Integrated DevOps, Data Aggregation, User-Centric Design, user engagement, robust security, Continuous Integration/Continuous Deployment (CI/CD)

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 Abstract

Holistic Assessment demonstrates one of the many reasons a value-based education is worth considering. It orients students to become lifelong learners. It emphasizes the focus on deeper learning instead of simply imparting concrete knowledge and textbook material. Holistic Assessment recognizes that educating a child goes beyond academics by promoting the growth of all areas of human development, including intellectual, emotional, social, and moral arenas. The future ji of students are shaped primarily by teachers through the use of holistic assessments, learning, and other teaching methods. Reflection on one's actions and how they might affect the local and global community is a skill that is taught to students.

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 Keywords

HOLISTIC, ASSESTMENT, STUDENTS, PARENTS, STAKEHOLDERS

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This paper presents the development of a full stack social media website utilizing MongoDB, Express.js, and Node.js (MEN stack).Leveraging the flexibility and scalability of MongoDB as a NoSQL database, coupled with the robustness of Express.js and Node.js for server-side development, the platform offers a dynamic and responsive user experience.

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MongoDB, Node, JavaScript, Socket.io

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The Insolvency and Bankruptcy Code (IBC) 2016 serves as a comprehensive guideline for the design, construction, and maintenance of buildings across India. This paper aims to provide an examination as to whether the inception of the code has been successful or not?

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CIRP, IBC, NCLT, PPIRP

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As the prevalence of deepfake videos continues to escalate, there is an urgent need for robust and efficient detection methods to mitigate the potential consequences of misinformation and manipulation. This Project explores the application of Long Short-Term Memory (LSTM) networks in the realm of deepfake video detection. LSTM, a type of recurrent neural network (RNN), has proven to be adept at capturing temporal dependencies in sequential data, making it a promising candidate for analyzing the dynamic nature of videos. It also addresses challenges and limitations inherent in deepfake detection, including mitigating false positives and negatives, and discusses potential avenues for future research to enhance the robustness of LSTM-based detection systems.

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 Keywords

Long Short-Term Memory (LSTM), Recurrent Neural Network (RNN), Generative Adversarial Network (GAN). Convolutional Neural Network (CNN).

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 Abstract

Statistical regression is vital for thoroughly analyzing and optimizing Internal Combustion engine performance, serving various functions like providing predictive insights and aiding data-driven decision-making. In this study, two methodologies, no transform and square root transformation are compared for their effectiveness in predicting engine performance indicators brake thermal efficiency and specific fuel consumption in spark ignition engines fueled with pyro oil and gasoline blends. Analysis of Variance (ANOVA), the statistical analysis tool was used to find the significant of the model. The findings consistently favor the square root transformation, which demonstrates higher R-squared values and better alignment with actual values compared to no transform regression technique. Notably, it offers more accurate predictions of critical metrics such as brake thermal efficiency and specific fuel consumption compared to the traditional no transform approach. Overall, this research significantly contributes to refining engine performance prediction models, offering valuable insights for decision-making in automotive engineering and design.

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 Keywords

Statistical regression, spark ignition engine, no transformation, square root transformation

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Creative Commons Attribution 4.0 and The Open Definition

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It is well said, "Literature is the mirror of the society." Through literature we can see the real face of a society. Literature and society are influential on each other. Indian literature as such in the first half of 20th century was greatly influenced by her struggle for independence. The present paper is based upon a study on the 'influence of Gandhi and his ideology on Indian fiction nearing her independence and after'

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Gandhi, ideology, fiction, realism, character, theme, struggle, independence.

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A customized e-commerce mobile application is tailored to the specific needs and preferences of a business, al- lowing for a personalized shopping experience for customers.The application incorporates mature e-commerce business processes and mobile technology to make it easy for businesses to set up and manage their online shop.The application is developed by identifying and examining the main features of existing commerce mobile applications, designing an architecture that supports rapid customization, and building a prototype using available related technology.The benefits of the application are two-fold, providing quick and easy setup for sellers and a seamless and personalized shopping experience for customers.The application provides valuable insights and analytics on customer behavior, which can be used to make data-driven decisions and improve operations.The flexible and scalable nature of the application makes it ideal for businesses of all sizes, allowing them to tap into the growing e-commerce market and reach their customers on the platform they use most. Index Terms--Business processes, Mobile technology, E- commerce market

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 Keywords

E-commerce mobile application; M-commerce Mobile commerce applications; Customizable e-commerce mobile application; Business processes Mobile technology ;E-commerce market; Personalized shopping experience; Customer behavior; Data-driven decisions; Security concerns ;Encrypted transactions

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Creative Commons Attribution 4.0 and The Open Definition