Volume 13 | Issue 3 |

 Abstract

This paper describes about the famous tourist place Lepakshi temple which is famous on the name of the village. The temple is dedicated to Virabhadhra swami. This temple is located in a village Lepakshi in Hindupur district. The temple is dated to Vijayanagara dynasty and became famous place for best repository for Paintings and Sculptures. It is one of the Iconic temples in terms of art, archeological and Tourism point of view. Author described restricted to describe the temple from tourism point of View. The important features of this temple are Nagalinga, Ganesha statue, Paintings and Sculptures in natyamandapa and mahamandapa, marvelous sculptures in unfinished Natyamandapa, monolithic Nandi and Jatayu park are salient features to drag attention of thousands of visitors. Now the department of tourism, Govt of Andhra Pradesh taking to develop and creating more facilities for visitors and organizing Lepakshi festival in grand scale.

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 Keywords

Lepakshi, Vijayanagara, Virupanna, Virabhadhra, Asia, Monolithic Nandi, Jatayu

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

For centuries, there has been fervent contention regarding the historical authenticity of Jesus. Critics and skeptics have raised numerous charges due to the absence of unequivocal evidence beyond biblical sources. Establishing trustworthy historical evidence for Jesus necessitates more than the mere reliability of the Bible. Since the Enlightenment in the 18th century, the examination of the historical Jesus has been laden with skepticism. Numerous contemporary critical scholars have meticulously examined the portrayal of Jesus in the New Testament and have published a confidential declaration asserting that the Jesus shown in the NT is not the historical figure, as there is insufficient external evidence to support this claim. This article explores the historical relevance of Jesus' life as Christians endeavour to present persuasive evidence of his existence beyond biblical texts. Consequently, in this writing, I provide robust evidence from non-biblical texts to substantiate the historical credibility of Jesus Christ and examine his presence outside the New Testament.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Historical Jesus, Mythicists, Gnosis, Romans, Gospel, Jewish, Gentiles, Pagan, and others.

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Creative Commons Attribution 4.0 and The Open Definition

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This research paper explores symbolism and supernatural elements in Samuel Taylor Coleridge's The Rime of the Ancient Mariner, focusing on the albatross as a Christ-like figure. The killing of the albatross is analyzed as a symbolic representation of original sin, disrupting the harmony between humanity, nature, and the divine, leading to supernatural punishment and suffering. The Mariner's journey mirrors Christian concepts of sin, guilt, atonement, and redemption, with the albatross serving as a divine intervention and its death symbolizing humanity's rejection of Christ. The paper further connects the Mariner's punishment to the biblical story of Cain, emphasizing the parallels in guilt, divine justice, and the burden of transgression. Ultimately, this analysis highlights the ecological and spiritual dimensions of the poem, reinforcing the idea that respecting nature is intertwined with respecting the divine order.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Coleridge, supernatural, harmony, biblical, and redemption

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project proposes a machine learning-based surveillance system for detecting traffic violations, specifically triple riding on motorcycles, using a Raspberry Pi platform. Triple riding, where three individuals share a single motorcycle, is a common violation that poses serious safety risks on the roads. The system automates the detection of such violations through real-time image processing, assisting law enforcement agencies in efficiently monitoring and managing traffic infractions. The system uses the affordability and computational power of the Raspberry Pi, paired with a camera module for capturing live video footage. The OpenCV library forms the core of the system, employing Haar Cascade Classifiers to identify motorcycles and their riders. Real-time processing of video frames by the detection algorithm counts the number of riders per motorcycle and triggers alerts when it detects more than two riders, a sign of triple riding. The anticipated outcomes include accurate and real-time detection of triple riding with minimal false positives, scalability across multiple locations, and integration with broader traffic safety and smart city initiatives. This automated detection system enhances traffic law enforcement capabilities and contributes to safer road conditions by deterring dangerous riding behaviours.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Raspberry pi, Open CV, Python, Triple Riding Detection, Helmet Detection, YOLOv3, Object Detection, Machine Learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Globally, as environmental protection concerns develop, sustainability has become more important in all spheres of company operations. Scholars from all around the world have undertaken a great deal of research and study on the topic of financing sustainable business practices. The term "green financial investment products" has been used to describe these funding mechanisms. This study aims to identify the most researched components of green financial investment products by reviewing the literature written by scholars and academicians worldwide between 2017 and 2023. The study's conclusions show that there is a significant amount of skewness in the research on green financial investment products, and there is comparatively less focus on connecting new tech-enabled investment products, such as cryptocurrencies, to sustainability issues. As far as green financial investment products are concerned, research on green cryptocurrency markets has been found to receive less attention than research on green bonds. The results of this study will be useful in directing future research on the market for green cryptocurrencies and way forward to develop the same.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sustainability; Investment Products; Market, Green Cryptocurrencies

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT The advent of telemedicine has revolutionized healthcare delivery, offering unprecedented flexibility and accessibility for medical professionals and patients alike. This study explores the dual impact of telemedicine on the work-life balance of healthcare providers, with a particular focus on women doctors. While telemedicine enhances flexibility by enabling remote consultations and reducing travel time, it also blurs the boundaries between personal and professional life, leading to potential burnout. The research investigates key challenges such as constant connectivity, increased patient demands, and technical adaptability, alongside benefits like improved time management and work flexibility. By analyzing case studies and conducting surveys among women doctors across various regions, this study seeks to identify best practices and institutional policies that can optimize telemedicine for achieving a sustainable work-life balance. The findings aim to provide actionable insights for healthcare organizations and policymakers to promote well-being and efficiency in the era of digital healthcare

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Telemedicine, Burnout, Reducing, work-life balance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Tourism has emerged as a significant driver of economic growth and entrepreneurship development in Kerala, particularly in the accommodation sector. The state's diverse attractions, including backwaters, hill stations, beaches, and cultural heritage, have led to an increasing influx of domestic and international tourists. This has created vast opportunities for entrepreneurs to establish and expand businesses in the hospitality industry, including hotels, resorts, homestays, and eco-lodges. This study examines the impact of tourism on entrepreneurship development in Kerala's accommodation sector by analyzing its economic, social, and environmental contributions. It explores how tourism-driven entrepreneurship has facilitated job creation, revenue generation, local industry growth, and sustainable business practices. Additionally, the study discusses the role of government policies, technological advancements, and responsible tourism initiatives in fostering entrepreneurship in the sector. While tourism has significantly contributed to economic diversification, challenges such as financial constraints, regulatory hurdles, and market competition persist. The study concludes that by leveraging innovation, sustainability, and community-based tourism, Kerala's accommodation sector can continue to drive economic growth while ensuring long-term environmental and cultural preservation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tourism, Entrepreneurship Development, Accommodation Sector, Kerala Tourism

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research explores key factors in job seeking, including digital platforms, AI-driven recruitment, and employer branding. It examines challenges like skill gaps, competition, and hiring biases. The study provides insights to optimize job search strategies and improve employment outcomes.

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Creative Commons Attribution 4.0 and The Open Definition

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AI (Artificial Intelligence)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The increasing demand for sustainable infrastructure has driven the need for innovative and eco-friendly construction materials. This study explores the potential of recycled mine waste and iron ore tailings (IOT) as alternative materials in pavement construction. The disposal of mining by-products poses significant environmental concerns, including land degradation and water pollution. Utilizing these industrial by-products in pavement applications not only addresses waste management challenges but also enhances pavement performance. The research focuses on evaluating the mechanical, durability, and environmental properties of pavement layers incorporating mine waste and IOT. Laboratory tests, including California Bearing Ratio (CBR), Marshall Stability, Unconfined Compressive Strength (UCS), and Durability Index, were conducted to assess the suitability of these materials. The results indicate that incorporating mine waste and IOT improves load-bearing capacity, moisture resistance, and long-term durability while reducing the reliance on natural aggregates. Additionally, a comparative economic and sustainability analysis demonstrates the cost-effectiveness and environmental benefits of this approach. The findings suggest that recycled mine waste and IOT can be effectively used as substitutes in pavement layers, contributing to sustainable road construction practices. This study provides valuable insights into waste reutilization and encourages the adoption of green engineering solutions in the transportation sector.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Pavement Performance, Recycled Mine Waste, Iron Ore Tailings, Sustainable Construction, Waste Utilization, Road Durability.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Soil evaluation and crop selection is a rapidly advancing domains that equips farmers with the expertise to determine the most suitable crops for their land and climate. Machine learning approaches to play a crucial role in automating crop recommendations and detection pests, enabling farmers to optimize their harvests. By utilizing seven distinct machine learning models, soil assessment, crop selection and yield forecasting are demonstrated. This paper presents an overview of ML techniques for soil classification, health monitoring and crop suitability assessment, focusing on their implementation in precision farming. Therefore, we proposed a system that can be highly beneficial for farmers and the general public by forecasting suitable crops for different soil types based on agricultural data analysis through machine learning, ultimately enhancing productivity and sustainability.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Soil analysis, Crop recommendation, Random Forests, Support Vector Machines, Machine learning, Sustainability.

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Creative Commons Attribution 4.0 and The Open Definition