Volume 13 | Issue 11 |

 Abstract

The increasing presence of microplastics in aquatic environments has become a major environmental concern due to their harmful effects on ecosystems and human health. Traditional methods of detecting microplastics are time-consuming, labor-intensive, and prone to human error. To address these limitations, this project proposes an AI-based microplastic detection system using deep learning techniques. The system utilizes image datasets of microplastic particles, which are preprocessed and annotated for training a YOLOv8 deep learning model to automatically identify and highlight microplastic particles in images. The model enhances detection accuracy by learning complex visual patterns and distinguishing microplastics from other impurities. Experimental results demonstrate that the proposed approach achieves fast, reliable, and precise detection, making it suitable for real-time environmental monitoring and research applications. This work showcases the potential of artificial intelligence in advancing environmental sustainability through automated microplastic detection.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Microplastic Detection, Deep Learning, YOLOv8, Artificial Intelligence, Image Processing, Environmental Monitoring, Object Detection, Computer Vision

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study focuses on identifying and preserving the rich cultural fabric layer of Devaliya by documenting both the physical landmarks and the living traditions surrounding it. The paper explores how Traditional Knowledge Systems (TKS) continue to shape the way a community is living and sustaining life in the physical realm, particularly in the face of urban modernization and gentrification. By safeguarding the unique stories, customs, and the nature - human practices, this research aims to protect Devaliya's cultural layer.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Traditional Knowledge Systems; Cultural Heritage; Rural Sustainability; Architecture; Ecology; Community Practices

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Structured teaching programme, Respiratory health hazards, Agriculture workers, Knowledge, Practice, Indore, Madhya Pradesh

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The fifth generation (5G) network delivers ultra-high data rates, massive connectivity, and low-latency services essential for applications such as autonomous systems, smart cities, and industrial automation. However, the rapidly fluctuating traffic demands and heterogeneous service requirements create significant challenges for efficient allocation of limited network resources. Static allocation strategies lead to congestion, uneven performance, and inefficient spectrum usage. To address these limitations, the study focuses on an AI-driven adaptive orchestration approach that dynamically optimizes resource distribution in 5G environments. A nested neural decision model combined with a Markov decision process enables intelligent prediction of traffic patterns and proactive re-allocation of resources in real time. The system supports QoS-aware decision-making across network slices, ensuring fairness, reduced delay, and enhanced throughput. Simulation-based analysis demonstrates improved resource utilization efficiency, minimized latency, and better user experience when compared to conventional allocation techniques. This study highlights the significance of autonomous learning-based resource management for advancing next-generation mobile communication networks.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

5G Networks, Dynamic Resource Allocation, Network Slicing, Nested Neural Networks, Markov Decision Process, AI-Driven Optimization, Quality of Service (QoS), Adaptive Scheduling.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the evolving landscape of modern computing, traditional operating systems bound to local hardware are increasingly being replaced by cloud-native solutions. This project proposes a cloud-based operating system that delivers secure, scalable, and platform-independent access to computing resources. By leveraging cloud infrastructure, the system enables users to interact with a personalized desktop environment, access applications, and manage data remotely from any internet-connected device. The architecture of the cloud-based operating system integrates the graphical intuitiveness of conventional desktop platforms with the modularity and flexibility of open-source systems. It employs virtualization, containerization, and centralized storage to support features such as remote desktop access, real-time data synchronization, and backend development capabilities. These features facilitate seamless collaboration, reduce hardware dependency, and enhance user mobility across devices and networks. Security is a foundational aspect of the system, incorporating encrypted communication channels, multi-factor authentication, and role-based access control to safeguard user data and system integrity. The operating system also provides developer-friendly APIs and SDKs for integration with cloud services, making it suitable for academic institutions, startups, and enterprise environments seeking cost-effective and scalable computing solutions. By abstracting the operating system from the physical hardware layer and hosting it in the cloud, this project contributes to the paradigm shift toward decentralized, service-oriented computing. The proposed cloud-based operating system aligns with emerging trends in edge computing, hybrid cloud deployments, and digital workspaces, offering a future ready platform that bridges usability, flexibility, and innovation.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud-based operating system, virtualization, remote access, platform independence, real-time sync, security, scalability..

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Teacher-parent collaboration is a crucial element in improving children's academic performance, social behavior, and emotional development during primary education. The partnership between home and school ensures continuity in learning, creates a supportive environment, and strengthens communication about children's progress. This paper explores the importance of collaborative relationships between teachers and parents in promoting student achievement. Drawing from ecological systems theory and family engagement frameworks, it highlights the role of trust, communication, and shared responsibility in child development. The paper also discusses barriers to effective collaboration and provides strategies for schools to build stronger partnerships with families to foster holistic growth in young learners.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Parent Involvement, Teacher-Parent Collaboration, Primary Education, Family Engagement, School Partnership, Communication

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The semi-arid region of Ananthapuramu, located in Andhra Pradesh, India, faces significant challenges in agriculture due to water scarcity, erratic rainfall, and soil degradation. Despite these challenges, horticulture offers high-value crops that have the potential to boost rural livelihoods. This paper discusses sustainable horticultural practices in Ananthapuramu, examining the agro-climatic conditions, current practices, and challenges such as water scarcity, pest management, and market access. It highlights government initiatives, NGO interventions, and the role of technology in improving productivity. The paper also explores future prospects for horticulture, focusing on crop diversification, water management, value addition, and technological innovations. Recommendations for enhancing institutional support and farmer empowerment are provided. The findings suggest that Ananthapuramu can be a model for sustainable horticulture in semi-arid regions through integrated approaches and climate-resilient farming practices.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sustainable agriculture, horticulture, semi-arid, Ananthapuramu, climate-resilient farming, water management, crop diversification

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Adolescents, Electronic devices, Health hazards, Knowledge, Video-assisted teaching programme

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Paranoid Personality Disorder, Knowledge, Attitude, Family Members, Mental Health Nursing

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: Internet Gaming Disorder, Awareness Programme, School Children, Behavioral Addiction, Digital Health

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Creative Commons Attribution 4.0 and The Open Definition