Volume 11 | Issue 5 |

 Abstract

Through the prism of translations, the present research explores how Italy morphed from a geographical region to a nation-state. The study underlines the essential role of human geography in the building of the Italian identity by looking at the dissemination of knowledge through translations. The difference between geography and space is stressed, as well as the way geographies influence language development. Consequently, the formation of a common language reinforces Italy's sense of nationalism. The findings of the study have substantial ramifications for analysing the intricate relationships between geography, language, and the emergence of nation-states.

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 Keywords

Translations, Space, Geography, Language Formation, Nationalism, Knowledge Dissemination

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This paper analyzes the selected short stories of Rabindranath Tagore, written at a time when feminism was not a well-developed concept. India, in the 19th and 20th centuries, when Tagore wrote, was a deeply patriarchal, oppressive and stifling society. Tagore was a philosopher, educationist, writer, artist, social reformer, and intellectual -all rolled into one- who used the medium of literature to bring about changes in society, which greatly influenced the national leaders like Mahatma Gandhi. This paper examines five short stories of Tagore: "Exercise-book", "Profit and Loss", "Giribala", "Judge" and "The Skeleton". Tagore strongly advocates for the education of women, as an essential condition for their upliftment. He supports the movement of women from the stifling four walls of their homes to the forefront of society, to take up roles that were a faraway dream till then. He stands against the evil practices like dowry system which commodify women and put a price to their life, freedom and dignity. He also comments on the condition of widows of the time, who were cursed to a life time of loneliness and abuse and neglect. We can see in Tagore's works powerful anticipations of the feminist thrust which from the second half of the 20th century onwards was gaining momentum on a global level as a movement advocating equal rights and opportunities for women and for their ultimate liberation from enslavement and misery in different guises. Through his works he gives voice to the voiceless and, from a larger humane perspective as a trail blazer which was to cater to greater cultural consequences quite progressively in later decades leading to larger perspectives on women's liberation.

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 Keywords

Tagore, feminism, women in India, education, gender, equality, culture, liberation

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Creative Commons Attribution 4.0 and The Open Definition

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Tunnels are part of modern transportation infrastructure systems, varies Tunnelling systems are used in railways, metro transport and even with road transport systems. The most common methods are NATM and TBM tunnelling methods. The durability and economical way of Tunnelling is the demand of today's infrastructure development. TBM tunnelling method with precast segments are used to build the required Tunnel. The precast segments are normally built with reinforced cement concrete at specified casting yards. Studies and research are going on replacing the conventional reinforced segments with steel fiber reinforced segments. SFRC segments offer economic advantages and address durability concerns related to corrosion in traditional reinforced concrete segments.

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 Keywords

NATM- New Austrian Tunnelling Method, TBM- Tunnel boring Machine, SFRC- Steel fiber reinforced concrete, MSFRC- Macro steel fiber reinforced concrete

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Creative Commons Attribution 4.0 and The Open Definition

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Music recommendation systems play a crucial role in today's digital music era, helping users discover new music based on their preferences. In recent years, Convolutional Neural Networks (CNN) have gained popularity in various domains due to their ability to capture hierarchical and local features from data. This survey paper provides an overview of personalized music recommendation systems using CNN, including a literature review of existing approaches, a detailed explanation of CNN, dataset and feature extraction, CNN-based music recommendation approaches, evaluation metrics and experimental results, challenges, future directions, and conclusion. The survey highlights the potential of CNN in enhancing the accuracy and effectiveness of personalized music recommendation systems and identifies areas for future research.

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Convolutional Neural Networks, Music Recommendation, Personalization, Deep Learning

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 Abstract

Natural Language Processing (NLP) is an interdisciplinary field that focuses on the interaction between human language and computers. With the increasing amount of data being generated every day, NLP has become an important tool for analyzing and understanding text data. Recently, pre-trained language models have gained attention in NLP due to their ability to learn from large amounts of text data and achieve state-of-the-art results in various NLP tasks. In this research paper, we investigate the effectiveness of pre-trained language models, such as BERT and GPT-2, in several NLP tasks, including sentiment analysis, text classification, and named entity recognition. We compare the performance of these models with traditional machine learning algorithms and rule-based approaches. Our experiments show that pre-trained language models outperform traditional machine learning algorithms and rule-based approaches in most NLP tasks, achieving high accuracy and F1 scores. Additionally, we explore the impact of fine-tuning pre-trained models on different datasets and analyze the performance of different fine-tuning strategies. Our findings suggest that pre-trained language models are effective in NLP tasks and can be used as a powerful tool for text analysis. Moreover, the performance of pre-trained models can be improved by fine-tuning on specific tasks and datasets. Our research contributes to the understanding of the capabilities and limitations of pre-trained language models in NLP and provides insights for future research in this area.

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 Keywords

Natural Language Processing, Pre-trained Language Models, BERT, GPT-2, Sentiment Analysis, Text Classification, Named Entity Recognition.

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Creative Commons Attribution 4.0 and The Open Definition

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The rise of online platforms and e-commerce has revolutionized consumer behavior, making product reviews a vital source of information for purchasing decisions. However, the prevalence of fake reviews has undermined the credibility and trustworthiness of online reviews, leading to the need for effective fake review detection systems. This research paper presents a novel approach to address this challenge by leveraging supervised machine learning techniques for the detection of fake reviews. The proposed system begins by constructing a comprehensive dataset consisting of genuine and fake reviews, along with relevant features such as review text, reviewer information, and rating patterns. These features are carefully selected to capture the distinguishing characteristics of fake reviews, including the presence of biased sentiments, unnatural language patterns, and inconsistent reviewer behavior. A supervised machine learning model, such as a support vector machine (SVM), KNN,Logistic Regression is trained on the labeled dataset to learn the complex patterns and relationships between the review features and their authenticity. The model undergoes an iterative process of feature engineering, selection, and hyperparameter tuning to optimize its performance.

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 Keywords

Supervised Machine Learning, SVM, KNN, Logistic Regression, Labeled Dataset, Hyperparameter, Fake Reviews

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Creative Commons Attribution 4.0 and The Open Definition

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The main objective of this study is to assess the perceived stress, adjustment and quality of life among parents of differently abled children. For this, comparative-experimental research was designed, with the sample of 100 parents including 50 fathers and 50 mothers. Perceived Stress Scale (PSS) by Sheldon Cohen, Global Adjustment Scale (GAS-Adult form) by Dr. Sanjay Vohra, & Quality of Life Scale (QOLS) by John Flanagan was used for data collection. The results showed that there are average levels of perceived stress and average levels of quality of life among parents of differently abled children. Also, they had good levels of social adjustment, average levels of emotional adjustment and occupational adjustment, poor levels of family adjustment and sexual adjustment, and unsatisfactory levels of health adjustment. It was also found that there is no significant difference in the levels of adjustment issues among father and mothers of differently abled children.

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Parents, Differently abled children, Stress, Adjustment ,Quality of life

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The prevalent notion regarding superstitions is that they possess a mystical or paranormal potency capable of exerting a direct impact on an individual's existence. The belief that certain rituals or abstentions from specific actions can ward off ill-fate or invite good luck is commonly held by a considerable number of individuals. These beliefs, commonly referred to as superstitions, are primarily rooted in cultural or religious customs, lacking in any logical or empirical basis. In these films draw on various theoretical perspectives to explore the themes of gender-based discrimination, superstition, and tradition versus modernity. One of the theoretical frameworks employed in the films is psychoanalytic theory, which seeks to explore the unconscious mind and the impact of past experiences on an individual's behaviour and psyche. Another theoretical perspective utilized in the films is magical realism, which blends elements of fantasy and reality to create a unique narrative that comments on contemporary issues. Folklore is also a prominent theoretical framework used in films. Finally, the films also explore feminist theory, which seeks to examine and challenge gender-based discrimination and oppression. The two Bollywood films under consideration in this study are "Stree" and "Bulbbul," directed by Amar Kaushik and Anvita Dutt Gupta, respectively. This research aims to analyse how the portrayal of mythological themes in two films, namely "Stree" and "Bulbbul," relates to both superstition and reality. The study also aims to investigate the depiction of female identity within societal contexts in these films. Specifically, the research seeks to examine how the films represent and contextualize myths, beliefs, and practices related to gender, patriarchy, and power dynamics in society. The analysis will explore how the representation of such themes in these films contributes to a broader understanding of the role of popular media in shaping perceptions and attitudes towards these issues. This research seeks to investigate the persistent significance of certain themes, such as violence, sexual assault, oppression, and patriarchy, in contemporary patriarchal representation in two Bollywood films, "Stree" and "Bulbbul." The research aims to examine how these films provide a realistic portrayal of the treatment of women in patriarchal societies and explore the complex interplay between gender, power dynamics, and societal norms. Additionally, this study aims to analyse how the films depict the sensitive topic of child marriage, the myth of the "chudail," and related prejudices. The research will delve into how the films navigate these issues and contribute to broader discussions and understandings of them.

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 Keywords

superstitions, beliefs, rituals, cultural customs, mythological themes, portrayal of gender, societal discussions

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The market is flooded with text mining and visualization tools that make it easier for creative individuals to find "hidden nuggets" of knowledge regarding developing technology. Every year, more and more data are produced, necessitating the need to synthesize and gather knowledge from an ever-expanding body of literature. In the corporate world, time is more valuable than money, so it takes a lot of time to comprehend what the data actually is, why it was developed, and why it is important. In this paper, we describe a case study of text analytics and data visualization using computational techniques like Natural Language Processing (NLP). This data can occasionally be found in an unstructured text format, which falls under the category of big data and has to be analyzed to yield useful information. This project uses Python libraries to process a large volume of text and provide graphical visualizations and text analysis operations such as Word cloud, Mendenhall Curve, Tokenization, Graph, Processed Text, and Name Entity Recognition (NER). The project shows that text analytics based on NLP is an effective method for comprehending the Data. To save time wastage and effort, this paper makes an effort to give a complete assessment of the data and to make appropriate data-driven judgement. This method allows the user to know the data and revise grammar simultaneously, which may be valuable for meetings, analysts, employees, students, and teachers.

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 Keywords

Text mining, text analytics, visualization, NLP

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Creative Commons Attribution 4.0 and The Open Definition

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Behavior is caused. Even spending behavior too. Various factors influence the behavioral aspects of raising finance, investment pattern, and even personal finance. A person's value system, beliefs, upbringing, family pattern, education, occupation and others influence his personal finance. The present study is an attempt to examine whether there is any association between a person's background and use of credit cards. Our study indicates that there is an association between credit card spending behavior and educational qualifications, occupation, gender and whether one's spouse is employed or not. On the contrary, this sort of association was not found between the spending behavior and credit card issue bank, religion and number of dependents.

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 Keywords

Credit card, Bank, Spending behavior, Personal finance, Myth

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Creative Commons Attribution 4.0 and The Open Definition