Volume 13 | Issue 12 |

 Abstract

Employer branding has emerged as a strategic human resource practice that significantly influences the attraction and retention of young talent, especially Generation Z. As Gen Z enters the workforce, their job preferences differ from previous generations, emphasizing organizational culture, work-life balance, career growth, and employer reputation. This study examines the impact of employer branding on Gen Z job preferences. A descriptive research design was adopted, and data were collected from 120 Gen Z respondents using a structured questionnaire. The study analyses key employer branding factors such as organizational culture, compensation, career development, work flexibility, and corporate social responsibility. The findings reveal that employer branding plays a crucial role in shaping Gen Z's employment decisions. The study provides insights for HR professionals to design effective employer branding strategies to attract Gen Z talent.

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 Keywords

Employer Branding, Generation Z, Job Preferences, Talent Attraction, HR Strategy, Organizational Culture

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper presents a detailed design and implementation of an AI-powered Tournament Management Agent based on Agentic Artificial Intelligence. Traditional tournament management relies on manual coordination or static software systems, leading to inefficiencies, data inconsistency, and limited scalability. The proposed system introduces an autonomous conversational agent capable of understanding natural language queries and executing tournament management tasks such as creation, updating, deletion, and retrieval of tournament information. The system integrates FastAPI for backend services, SQLite for lightweight persistent storage, and Google Gemini for natural language understanding and reasoning. By combining CRUD-based automation with agentic decision-making, the system significantly reduces human effort and improves usability. Extensive testing and analysis demonstrate that the proposed approach enhances operational efficiency and provides a scalable solution suitable for academic institutions, sports clubs, and event organizations.

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 Keywords

Agentic AI, Tournament Management System, Artificial Intelligence, FastAPI, SQLite, Natural Language Processing, AI Agents, Gemini

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 Abstract

This study examines the factors that influence hotel selection in metropolitan markets, with specific reference to Holiday Inn Mumbai International Airport. Mumbai represents one of the most competitive hospitality environments in India, where hotels must go beyond brand recognition to convert awareness into actual bookings. The research focuses on key determinants such as cleanliness, room comfort, location, pricing, service quality, brand reputation, loyalty programs and the role of digital platforms in shaping guest decisions. The study adopts a descriptive and quantitative research design using primary data collected through a structured online questionnaire administered to ninety respondents, including both guests who have stayed at the hotel and those who have not. Secondary data from academic journals and industry reports are used to support the analysis. The findings reveal a significant gap between brand awareness and booking behavior. While the Holiday Inn brand enjoys strong visibility, this does not translate proportionately into stays. Cleanliness, hygiene, comfort and accessibility emerge as the most influential decision factors, outweighing brand name alone. Digital platforms play a decisive role in the hotel selection process by supporting discovery, comparison and evaluation through online travel agencies and reviews. Guests who have stayed at the property report satisfaction with rooms and food and beverage services, while banquet facilities and marketing communication show lower visibility. The study concludes that to improve conversion, the hotel must strengthen its digital presence, reposition itself beyond a primarily business travel identity and leverage operational strengths to build loyalty. The research contributes practical insights for hospitality managers operating in highly competitive urban markets.

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 Keywords

Hotel selection, Holiday Inn Mumbai International Airport, Cleanliness and hygiene, Room comfort, Location convenience, Price and value, Brand reputation, Online travel agencies, Online reviews, Digital presence, Guest satisfaction, Loyalty programs, Marketing gap, Urban hospitality market

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Bahu Pratiman Hasthakshep Model Ka Vikas : Hindi Bhasha Me Aadharbhut Bhashai Kaushal Hetu

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Creative Commons Attribution 4.0 and The Open Definition

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Bahu Pratiman Hasthakshep Model Ka Vikas : Hindi Bhasha Me Aadharbhut Bhashai Kaushal Hetu

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Aahar Ka Prabhav: Sthaulya Ke Liye Ek Sampurna Drishtikon.

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Aahar Ka Prabhav: Sthaulya Ke Liye Ek Sampurna Drishtikon.

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 Abstract

Vaanabhatt Kee Drishti Se Naaree Kee Tapasya

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Vaanabhatt Kee Drishti Se Naaree Kee Tapasya

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Diabetic Retinopathy (DR) remains a leading cause of vision loss among diabetic patients globally, making its early detection and classification vital for effective treatment. Recent advancements in deep learning have shown significant promise in medical image analysis, particularly in ophthalmology. This paper proposes a comprehensive study on the application of transfer learning-based deep neural networks (DNNs) for the early detection and multi-stage classification of Diabetic Retinopathy using fundus images. Leveraging pre-trained convolutional neural networks such as VGG16, ResNet50, and InceptionV3, the model fine-tunes features to effectively classify the severity levels of DR, ranging from no DR to proliferative DR. The proposed approach is validated using benchmark datasets, achieving high accuracy, precision, and sensitivity, thereby demonstrating robustness in real-world clinical environments. The integration of transfer learning not only reduces the computational burden and training time but also enhances feature extraction capabilities, leading to improved diagnostic performance. This study emphasizes the potential of transfer learning-based DNNs as a reliable tool for ophthalmologists in the early detection and grading of Diabetic Retinopathy.

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 Keywords

Diabetic Retinopathy, Deep Neural Networks, Transfer Learning, Fundus Images, Early Detection, Classification, Convolutional Neural Networks, Medical Image Analysis, ResNet50, VGG16.

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Creative Commons Attribution 4.0 and The Open Definition

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Mosses (Bryophytes) are sensitive indicators of environmental variation due to their dependence on moisture, shade, substrate, and microclimatic conditions. Ranchi district of Jharkhand represents a mosaic of ecological habitats; however, bryophyte diversity in the region remains insufficiently explored. This study investigates the identification and external morphological variation of mosses collected from four distinct habitats: two from urban road side area and two from forest area. Moss samples were collected to identify and are examined for key morphological characters such as growth form, leaf architecture, colour, seta/capsule features, and substrate specificity. To study the external morphological response of moss during three seasons (summer, rainy, and winter) at four different locations for a period of one year. A total of four moss species belonging to three families were recorded. Species richness was highest in the moist riparian habitat and lowest in the urban habitat. Significant morphological plasticity was observed in species such as Entosthodon buseanus and Funaria hygrometrica, reflecting environmental stress gradients. The study highlights strong habitat influence on external morphology and underscores the importance of microhabitat conservation for maintaining regional bryophyte diversity.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mosses, Bryophytes, Morphology, Habitat variation, Species identification

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Evolution of Anti-Defection Law, 1985 in India and analytical study of defections and change of power in various states

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Creative Commons Attribution 4.0 and The Open Definition

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Evolution of Anti-Defection Law, 1985 in India and analytical study of defections and change of power in various states

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Creative Commons Attribution 4.0 and The Open Definition

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Intensification of land use and diversification of crop to multiply income generation, are the recent trends. During fieldwork, it was found that livelihood issues are overlooked because, there are ample evidence, where lack of basic needs, poverty and livelihood issues are rampant in rural Mizoram. Case studies of policy beneficiaries - cultivators, piggeries, poultry, fisheries, sugarcane farms and orchard farms and the outcomes of development policies initiated by state. The villagers opined that development policies are not effective, nor able to improve land use activities. The main objective of the study is to show the reproduction of poverty in upland in Mizoram. Why traditional livelihood cannot be altered and improvised for good? Examining the outcomes of privatization of community land is the scope, which the study wants to analyze during fieldwork. Examine the everyday livelihood hurdles. During fieldwork 2022, it was cleared that when community lands for farming got privatized, the outcome is the constriction of jhum land share for each household. Constriction of jhum land, intensification of land use and diversification of crops have been the emerging trends in the uplands.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Jhum, Development Policies, Community farmland, Privatization

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Creative Commons Attribution 4.0 and The Open Definition