Volume 12 | Issue 4 |

 Abstract

The Smart AI-Enabled Blind Stick emerges as a ground breaking assistive device, designed to empower visually impaired individuals with enhanced mobility through Artificial Intelligence (AI), advanced sensor integration, and GPS tracking. At its core, the device utilizes convolutional neural networks (CNNs) for precise object detection, alongside ultrasonic sensors for real-time obstacle identification, and GPS technology for accurate outdoor navigation. This integration facilitates seamless indoor and outdoor mobility, offering users audio, tactile, and vibrational feedback for immediate awareness and obstacle avoidance. Our innovative approach combines real-time environmental analysis with intuitive user feedback mechanisms, ensuring a high level of safety and independence for visually impaired users. The CNN model is trained on extensive datasets to recognize a multitude of obstacles, while the ultrasonic sensors fill in the gaps by detecting immediate, unforeseen obstructions. GPS functionality further enhances the device's utility, enabling destination setting and vocalized route guidance.

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 Keywords

Artificial Intelligence, GPS technology, Ultrasonic sensor, Object detection, Feedback mechanism.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Textiles and motifs play a significant role in reflecting cultural Heritage, folk culture, and symbolism. This study contextualizes the textiles and motifs within the broader framework of folklore in context. It examines the symbolic meaning and folkloric elements embedded within selected motifs from Delhi's textile tradition. Further, it outlines the role of textiles and motifs in soft power with certain examples from the G20 summit. Examined within the theoretical frameworks from cultural studies, the research aims to unwrap the cultural, social, and economic dynamics underpinning motif symbolism, production, and circulation. By synthesizing data collected from artisan field visits, literature surveys, and secondary sources, the study presents the cultural, mythological, and economic dynamics of selected motifs such as the Paisley, Lotus, Tree of Life, Elephant, Peacock, and Parrot. The findings reveal intricate meanings and cultural significance embedded within textiles and motifs, reflecting themes such as love, fertility, wisdom, resilience, etc. The research addresses the gap in understanding the intersection of textiles and motifs not only from the perspective of aesthetics and symbolism but with deep-rooted meanings, folk cultures, identity, heritage preservation (along with innovation), and soft power dynamics; overall, the research contributes to a deeper understanding of the cultural significance of textile and motifs, shedding light on their role as symbols of culture, identity, Heritage, craftsmanship, and diplomacy.

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 Keywords

Textiles, Motifs, Folk-Culture, Symbolism, Creativity, Craftsmanship, Soft Power, Heritage

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study explores the imperative for the Indian banking industry to embrace green capital as a catalyst for sustainable energy initiatives. With a focus on strategic financial investments, the paper underscores the urgency of aligning banking practices with India's environmental goals. By examining successful case studies, emerging trends, and regulatory frameworks, the research delineates the transformative potential of green investments. It highlights collaborative efforts between financial institutions, governmental bodies, and the private sector in driving sustainable energy projects. The abstract emphasizes the dual benefits of green capital - contributing to environmental conservation and generating long-term economic returns. The integration of environmental, social, and governance factors into financial decision-making processes is discussed, providing insights into risk mitigation. The study concludes by advocating for the Indian banking industry's pivotal role in reshaping the economic landscape through responsible and sustainable financial practices. This research aims to guide stakeholders in navigating the evolving green finance domain, fostering a resilient and eco-friendly trajectory for the Indian banking sector.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Green Capital, Sustainable Energy, Banking Industry, Strategic Financial Investments

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

At present days, Wireless sensor networks (WSNs) ensure and recognized in research and developmental sectors in several fields, like verbal exchange, farming, crop monitoring, smart fitness, logistics, and agriculture investigation and monitoring system. In the locality of agriculture construction, inter net of things plays a important role to inspect the crops situation and power up the agriculture accuracy with abundant sensors. All the sensors nodes are positioned in the lands to increase production of crops over smooth agricultural adoptions and obtain the data of concerning plants. Here proposed a swarm optimization technique using internet of things initially, the nodes receives all the information and data and choose a secure cluster heads. Furthermore, for efficient data transmissions is calculated using signal to noise ratio. Furthermore, at the time of data communication security is providing with the help of encryption technique. The results proves that the proposed method Efficient and Secured IOT based Agriculture Wireless Sensor network using Swarm Optimization is gives an better results compare with existing PSO method.

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 Keywords

Swarm optimization, IoT, Internet of Things, Security with IoT

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Paying guest accommodations, also referred to as PGs, are a typical kind of housing for young professionals, migrants, and students in urban areas across the globe. In these kinds of agreements, tenants are called paying guests and the rental of a room within a residential property, usually under the management of a landlord. PGs encourage social interactions and networking possibilities by providing a feeling of community and camaraderie among inhabitants. The current study aims to understand the issues, face by the migrants for searching suitable accommodation and analyse the feasible solution with respect to their requirements. The s

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AN ANALYSIS FOR THE NEED OF ACCOMMODATION FOR MIGRANT STUDENTS AND WORKING PROFESSIONALS: A CASE STUDY IN BANGALORE

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The rapid growth of e-commerce platforms has led to an overwhelming number of choices for consumers. Product recommendation systems have become essential tools for helping users navigate the vast product space. This project aimed to develop and compare various machine learning algorithms for product recommendation and enhance the user experience by providing detailed product information. The proposed method involved the implementation of six different algorithms: Singular Value Decomposition (SVD), SVD++, Alternating Least Squares (ALS), K-Nearest Neighbors with Z-score (KNNWithZScore), User-Based Nearest Neighbors (UBNN), Item-Based Nearest Neighbors (IBNN), and a Hybrid model. Each algorithm was evaluated based on several performance measures including RMSE, MAE, Precision, Recall, F1-score, Fit Time, and Test Time. The SVD++ model demonstrated superior performance and was selected for the final implementation. To make the recommendations more user-friendly, web scraping was employed to retrieve detailed product information such as name, description, properties, image, and product listing URL. The results suggest that the SVD++ model, combined with detailed product information, provides an effective and user-friendly product recommendation system. This project contributes to the ongoing efforts to enhance user experience on e-commerce platforms and paves the way for future research in personalized recommendation systems.

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 Keywords

E-commerce, Recommendation, Product Recommendation, Collaborative Filtering, Matrix Factorization, Machine Learning, SVD, RMSE, MAE.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the contemporary competitive business environments, Artificial Intelligence (AI) emerges as a pivotal component in Human Resource Management (HRM). Despite its longstanding presence as a concept, AI has garnered significant attention only recently. Serving as a sophisticated tool wielded by humans, AI holds the potential to revolutionize various aspects of HRM, including recruitment, training, and performance management. Through AI-powered solutions, HR departments can enhance employee service delivery while simultaneously optimizing costs. The integration of AI in HRM is increasingly vital, empowering organizations to bolster efficiency levels while concurrently elevating employee satisfaction. Overall, the combination of an exploratory research design, qualitative approach, and reliance on secondary data analysis enables this study to provide insight into the complexities of AI integration in HRM, offering valuable insights and implications for future research and practice. Consequently, researchers have focused on identifying key HRM tasks ripe for AI integration, aiming to amplify efficacy within HRM practices.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI in HRM, Artificial Intelligence, Application of AI in Human Resource, Human Resource Management, Human Resource Management Practices

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Pooyamkutty is a remote village situated along the Kuttampuzha river ,a tributary of Periyar.it is part of Western Ghats and it is close to Iravikulam National Park and Anamalai Tiger Reserve and they share boundary with Pooyamkutty. Podostemaceae is a unique rheophytic angiosperm family which is abundant in almost all the 44 rivers of Kerala.Presence of Western Ghats combined with the North-East and South -West Monsoons provide a sub-tropical climate and seasonal flooded mountainous rivers ideal condition for Podostemaceae.In the present survey,the investigators were able to gather 5 genera and 6 species of the Family Podostemaceae from different localities of Pooyamkutty:Indotristicha ramosissima, Dalzellia ceylanica,Polypleurum stylosum,P.prostratum , Podostemum subulatum and Zeylanidium lichenoides.

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 Keywords

Pooyamkutty, Podostemaceae, Indotristicha ramosissima, Dalzelliaceylanica,Polypleurum stylosum,P.prostratum , Podostemum subulatum, Zeylanidium lichenoides

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Creative Commons Attribution 4.0 and The Open Definition

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This research investigates the interplay between Big Five personality traits and mood regulation strategies facilitated by music. Utilizing the Mini-IPIP questionnaire, participants' levels of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness were assessed. Mood regulation strategies were evaluated through the Brief Mood Regulation through Music (BMMR) scale, covering dimensions such as Entertainment and Mood Maintenance, Revival, Strong Sensation, Diversion, Discharge, Mental Work, and Solace. Pearson correlation coefficients were computed to analyze the relationships between personality traits and mood regulation dimensions. The results unveiled significant positive correlations between Extraversion, Conscientiousness, and Openness to Experience with various mood regulation aspects. Furthermore, regression analyses highlighted Openness as a significant predictor across several dimensions, including Entertainment and Mood Maintenance, Revival, Strong Sensation, and Mental Work. These findings underscore the role of personality traits in influencing individuals' preferences for mood regulation strategies via music, providing valuable insights into the complex dynamics between personality and emotional regulation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Big Five personality traits, mood regulation, music, correlation analysis, regression analysis, emotion regulation.

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Creative Commons Attribution 4.0 and The Open Definition

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This research paper presents the design and analysis of a mechanical human hoist featuring a scissor mechanism. The objective of this study is to develop a safe and efficient lifting system for human or goods elevation in various applications as automobile workshops, logistics sectors, etc. The scissor mechanism, is a fundamental component of the hoist, enabling both vertical lifting and controlled descent. Detailed engineering and kinematics analysis are conducted to optimize the design for stability, reliability, and load bearing capacity. The system is powered by an electric motor and incorporates safety features to ensure user protection during operation. Key aspects covered in this project include the scissor mechanism's geometry, material selection, load bearing capacity, and control system. The hoist is designed with on focus ease of use, adaptability to different environments, and compliance with safety standards. The result of this study demonstrates the feasibility and effectiveness of the scissor mechanism based mechanical human hoist. It offers a versatile solution for vertical mobility, making it suitable for a wide range of applications, with a primary emphasis on enhancing the quality of life and safety for individuals in need of assisted vertical movement. This abstract summarizes the development and analysis of mechanical hoist system, highlighting its scissor mechanism as a key feature for vertical lifting.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mechanical Hoist

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Creative Commons Attribution 4.0 and The Open Definition