Volume 14 | Issue 6 |

 Abstract

Food Recommender Systems (FRS) has emerged as an important sub area of Computer Science and Engineering (CSE) that is significantly different from other traditional areas of recommendation such as e-commerce or media streaming. This systematic review aims to do an architectural analysis of intelligent FRS using Artificial Intelligence (AI) and Machine Learning (ML). We summarize 21 basic peer-reviewed studies and examine how these emergent systems cope with high dimensional and non-linear constraints like user health states, complex multi-component ingredients, temporal consumption rules, and multimodal streams of features. These methods fall into four structural paradigm groups: Traditional Matrix Methods, Sequence-based Neural Nets, Heterogeneous Information Networks (HIN), and Advanced Optimization Frameworks. Last, open challenges for sparsity training, cold-start issue and unified offline metrics for algorithmic precision nutrition are elaborated which will serve as future research roadmap.

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 Keywords

Food Recommender Systems, Heterogeneous Information Networks, Deep Learning, Multi-Objective Optimization, Computational Health.

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT To understand the progress and development of a society, one of the crucial indicator is how women in that society is being treated. What are their rights, what limitations and prejudices do they face and what opportunities do they have Women constitute half of the global population. However, they are the largest excluded category in almost all aspects. The status of women in tribal society, even in the era of globalization, remains one of the major issues for discussion. In most tribal societies across the world, women are considered a weaker section of society, though women contribute to the overall social development, which cannot be denied. It is generally said that women in the North-Eastern part of India enjoy a better status than their counterparts in the rest of India. However, the customary law and practices in their application are often discriminatory against them. Understanding gender dynamics in tribal societies requires looking beyond romantic notions to examine both freedom and constraints that shape women's lives. The objectives of this paper are to highlight and understand the status of women in the traditional Apatani society of Arunachal Pradesh, which has to be studied in the light of their work participation in social, economic, religious, and political spheres. The primary and secondary sources have been used in the collection of data.

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 Keywords

Keywords: Apatani, women, Arunachal Pradesh, Customary law

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

भारत विश्व के सर्वाधिक जनजातीय विविधता वाले राष्ट्रों में से एक है, जहाँ लगभग 10.45 करोड़ (2011 जनगणना) जनजातीय जनसंख्या 705 से अधिक जनजातीय समूहों में विभाजित है। ये समुदाय भारतीय सभ्यता की आदिम धारा के संवाहक हैं और देश के वन, जल, खनिज एवं सांस्कृतिक संसाधनों के प्रमुख संरक्षक रहे हैं। तथापि स्वतंत्रता के सात दशकों के पश्चात् भी ये समुदाय विकास की मुख्यधारा से पूर्णतः सम्बद्ध नहीं हो सके हैं। प्रस्तुत शोध पत्र में भारतीय जनजातीय समुदायों के ऐतिहासिक विकास-क्रम, उनके सामाजिक-सांस्कृतिक-आर्थिक योगदान तथा उनके समक्ष विद्यमान चुनौतियों का वैश्विक संदर्भ में तुलनात्मक विश्लेषण किया गया है। वेदकालीन साहित्य से लेकर NEP 2020 तक की जनजातीय नीतियों का परीक्षण करते हुए यह स्थापित किया गया है कि जनजातीय समुदाय भारत के सतत विकास (Sustainable Development) में अनिवार्य भागीदार हैं। अंतर्राष्ट्रीय अनुभवों — ऑस्ट्रेलिया, कनाडा, न्यूज़ीलैंड, बोलीविया — के आलोक में भारत के लिए नीतिगत सुझाव भी प्रस्तुत किये गए हैं।

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 Keywords

जनजातीय विकास, भारतीय जनजाति, वैश्विक स्वदेशी समुदाय, वन अधिकार अधिनियम, UNDRIP, सतत विकास, जनजातीय योगदान, IKS, पारंपरिक पारिस्थितिक ज्ञान, PESA, समावेशी नीति

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Creative Commons Attribution 4.0 and The Open Definition

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Social media platforms have emerged as one of the most transformative forces in contemporary society, fundamentally reshaping how individuals communicate, form identities, and navigate social norms. From an educational standpoint, understanding these dynamics is essential for equipping students, educators, and policymakers with the tools to engage critically and responsibly with digital environments. This paper examines the multidimensional role of social media in shaping social behavior, drawing on empirical evidence and educational theory. Quantitative data reveal that over 4.9 billion people globally use social media as of 2024, with teenagers spending an average of 7.2 hours per day on digital platforms. The paper explores five key dimensions: (1) identity formation and self-presentation, (2) peer influence and conformity, (3) civic engagement and social movements, (4) mental health and behavioral outcomes, and (5) implications for educational practice and digital literacy. Findings indicate that social media simultaneously fosters connectivity, creativity, and civic awareness while also contributing to social comparison, cyberbullying, misinformation, and addictive patterns. The paper argues that educational institutions must integrate structured digital literacy programs and social-emotional learning frameworks to help learners navigate the social media landscape constructively. The conclusion advocates for a balanced, evidence-based pedagogical approach that acknowledges both the opportunities and risks inherent in social media use, and calls for collaboration between educators, parents, platform designers, and policymakers.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

social media, social behavior, digital literacy, education, identity formation, mental health, civic engagement, peer influence.

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: Colour plays a significant role in the fashion industry and has a strong influence on consumer buying behaviour. This study focuses on understanding how colour trends affect customers' preferences and purchase decisions in Pune city. Colour is not only an aesthetic element but also a psychological factor that impacts emotions, perception, and product attractiveness. The research aims to analyse how consumers respond to different colour trends and how these trends influence their buying decisions. It also examines the role of colour in visual merchandising and its impact on boutique sales. Data for the study was collected through a structured questionnaire from consumers and boutique owners. The responses were analysed using percentage and graphical methods to identify patterns and trends. The findings of the study indicate that most consumers are highly influenced by colour while purchasing fashion products. Bright and trending colours are preferred, especially during festive and wedding seasons. Boutique owners also believe that colour trends play an important role in increasing sales and attracting customers. The study concludes that colour is a powerful tool in the fashion industry and should be carefully selected to meet consumer expectations. Understanding colour trends can help designers and retailers improve product appeal, enhance customer satisfaction, and increase sales. Therefore, the effective use of colour in fashion design and retail strategy is essential for success in the competitive market.

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Creative Commons Attribution 4.0 and The Open Definition

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Colour Trends, Consumer Behaviour, Fashion Industry, Buying Behaviour, Visual Merchandising, Retail Sales.

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Creative Commons Attribution 4.0 and The Open Definition

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Text-to-Speech (TTS) technology has become one of the most significant advancements in the field of Artificial Intelligence, Speech Processing, and Human-Computer Interaction. It enables computers to transform written text into natural and intelligible speech, allowing users to interact with digital systems more efficiently. However, conventional TTS systems are generally designed for a single language and fail to provide accurate pronunciation, natural intonation, and seamless language switching in multilingual environments. This limitation creates accessibility challenges for multilingual users, visually impaired individuals, students, travelers, and professionals who regularly communicate using multiple languages. The proposed Multi-Language Text-to-Speech Recognition System addresses these challenges by developing an intelligent speech synthesis framework capable of converting text written in different languages into clear, natural, and human-like speech. The system integrates Natural Language Processing (NLP), Deep Learning, Neural Text-to-Speech models, and language identification techniques to automatically recognize the input language before generating speech. Advanced preprocessing methods including text normalization, tokenization, phoneme conversion, and linguistic feature extraction are employed to improve pronunciation accuracy and speech fluency. The proposed framework supports multiple regional and international languages while preserving language-specific pronunciation, stress patterns, rhythm, and emotional tone. Unlike traditional TTS systems, the proposed solution can efficiently process multilingual documents without requiring manual language selection. Deep Neural Networks and Transformer-based architectures significantly improve speech quality while reducing robotic voice characteristics. Furthermore, the system is designed as a web-based application that provides an easy-to-use interface where users can enter text, select voice preferences, adjust speech speed, and download synthesized audio. Experimental evaluation demonstrates high speech intelligibility, pronunciation accuracy, naturalness, and reduced synthesis latency across different languages. The proposed system has potential applications in education, healthcare, e-learning, digital assistants, accessibility tools, customer support, smart devices, and multilingual communication platforms. Overall, the research contributes toward developing an efficient, scalable, and user-friendly multilingual speech synthesis system capable of enhancing digital accessibility and improving communication among users speaking different languages.

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 Keywords

Multi-Language Text-to-Speech, Artificial Intelligence, Natural Language Processing (NLP), Speech Synthesis, Deep Learning, Neural Networks, Transformer Models, Language Identification, Speech Processing, Human-Computer Interaction, Voice Generation, Accessibility, Multilingual Communication.

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Creative Commons Attribution 4.0 and The Open Definition

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This study examines the issue of financial exclusion in Tirupur highlights the gap that still exists between technological progress and ground-level realities. Despite advancements in digital finance and supportive government initiatives, a considerable section of the population--particularly workers in the unorganized sector--remains unbanked or underbanked.

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 Keywords

FinTech, Financial Inclusion, Unbanked Population, Digital Financial Services, Mobile Banking, Financial Literacy, Digital Payments, Inclusive Finance.

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Creative Commons Attribution 4.0 and The Open Definition

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A Study to assess the knowledge regarding impact of alcoholism among young adults residing in selected areas of Chengamanadu gram panchayath. The objective of the study was to assess the knowledge regarding the impact of alcoholism among young adult and find out the association between knowledge regarding the impact of alcoholism among young adults with their selected demographic variables. In this, a descriptive study design was used and 30 young adults were selected for the study. The data was collected by using structured questionnaire to assess the knowledge regarding impact of alcoholism in young adults. The data was analysed using descriptive statics. In the study, the knowledge was described as mean, standard deviation, frequency and percentage. The result shows that (43.3%) has adequate level of knowledge, (50%) has average knowledge, and (6.67%) has poor knowledge. The knowledge was mainly characterized as adequate, average and poor. According to the study there is a significant association between the knowledge and demographic variables such as age and socio-economic status of the participants and there is no association between other demographic variables.

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Keywords:-Assess, Knowledge, Impact of Alcoholism, Young Adults

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Abstract :- In this paper, we anelyze a Bianchi type-I cosmo logial model filled with bulk vicous fluid .string cloud with attached particals dust, and magnetic field wthin the framewomk,of,General Relativity. Balk viscocosity is considened to describe dissipative proceses in the early universe, whil cosmic strings represent topological defects strings represent topological defects formed during phase transitions. the presenc of a magnetic field equations are formulated and solved under suitable physical conditions. the behavior of physical parameter's such as energy density, expansion scalar, shear scalar, and magnetic field play a significant role in the evolution of the universe, leading to isothopization of later times.

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Keywords :- Bianchi type -I, Bulk visgosity , cosmic strings ,dust matter, magneticfield , genenal relativity.

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Creative Commons Attribution 4.0 and The Open Definition

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Micro, small, and medium-sized businesses are crucial to India's financial stability because they drive economic expansion, productivity, and job creation. The Goods and Services Tax, or GST, was designed to simplify taxation and provide clarity by utilising a single indirect tax structure. Under GST 2.0, modern digital techniques for tax compliance have been implemented, including electronic invoicing, automatic submission of tax forms, fast invoice matching, and monitoring information via the GST Network, or GSTN. However, many small and medium-sized enterprises struggle to utilise these digital tools due to their lack of digital expertise, inadequate equipment, and rising costs of regulatory compliance. This study aims to investigate how the digital advancements of GST 2.0 impact tax management for MSMEs in Nagpur, Maharashtra. A carefully designed questionnaire was used to collect first-hand information from 400 MSMEs for this study. The relationship between digital shifts and regulatory compliance is assessed using statistical techniques such as descriptive analysis, relationship analysis, multiple regression, and ANOVA. The findings are expected to demonstrate how MSME compliance is affected by digital tax obligations and highlight the primary challenges companies face while implementing digital GST systems. By suggesting strategies to enhance MSMEs' digital readiness and successful compliance, the report aims to influence policy.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

GST 2.0, MSMEs, Digital Tax Compliance, Compliance Behaviour, E-Invoicing, India

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Creative Commons Attribution 4.0 and The Open Definition