Volume 13 | Issue 4 |

 Abstract

Public libraries in Maharashtra play an important role in the dissemination of knowledge and the educational, cultural, and economic progress of society.This research thesis examines in-depth the various services provided by public libraries, their uses, impact, and future prospects.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Services provided by public libraries in Maharashtra

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Technical and Vocational Education and Training (TVET) is a key pillar in enhancing employment and a significant driving force for the sustainable and socio-economic growth of the nation. It contributes to achieving all the Sustainable Development Goals (SDGs). As per the 2011 census, the literacy rate of Nagaland is 79.6%, which is higher than the national rate of 73%. However, in PLFS 2022-2023, the Unemployment Rate (UR) is 4.3%, above the All-India average of 3.2%. Therefore, to enhance the employment rate in Nagaland, the quality of the TVET system needs to be improved by addressing its challenges. The present paper will analyze the status of Technical and Vocational Education and Training in Nagaland, focusing on the vocational education and training provided by the vocationalisation of school education, Polytechnic, Industrial Training Institutes (ITIs), and Private Vocational Training Providers (VTPs). It also aims to discuss its challenges and improvement strategies through the survey of existing research, government reports, and websites. In Nagaland, the TVET system has shown significant development. Despite all these developments, it continues to face challenges, including limited infrastructure, a shortage of qualified trainers, and the need for stronger industry linkages. Improving these issues is crucial for enhancing the quality and effectiveness of technical and vocational education in the state.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

challenges, strategies, Nagaland, TVET.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Feminist Foreign Policy, abbreviated as FFP, signifies a revolutionary stance bringing global governance under the rigorous ethos of gender equality and the dismantling of entrenched power hierarchies in international relations. This article explores the process of domestication of FFP in Sweden and Canada, two groundbreakers in this area of enforcement. It analyses how these countries operationalize FFP together with successes and challenges. At the end of this analysis, it is elucidated that the FFP has the potential to bring about lasting peace empowerment for marginalized sectors and address systemic inequities. Backed by global agendas such as Sustainable Development Goals (SDGs), the FFP provides pathways to achieving a more just and equitable world. The article ends on a call to extend the adoption of FFP, epitomizing its role in radically transforming global governance and addressing some of the most vexing challenges facing humanity. Through experiences in Sweden and Canada, this article establishes that FFP is necessary and achievable and serves as a model for others to replicate. By providing guidelines for a more just and equal world along with global agendas such as Sustainable Development Goals, the FFP opens up avenues to achieving further justice in the world. The article ends with the demand to make wider adoption of FFP possible, as it reshapes global governance and deals with some of the most worrying dilemmas facing humankind today. Within the Swedish and Canadian experiences, this article argues that FFP is necessary and achievable, serving as a model for replication by other states.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Feminist Foreign Policy (FFP), Gender equality, Intersectionality, Human security, Global governance, Systemic inequalities, Sustainable Development Goals (SDGs), Peacebuilding, Marginalized groups.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Serverless computing, which offers dynamic scalability, cost effectiveness, and streamlined infrastructure administration, has become a paradigm shift in cloud computing. In contrast to conventional cloud models, serverless architectures let developers concentrate only on running code while cloud providers manage resource allocation and upkeep. Notwithstanding its benefits, serverless computing presents particular performance and security issues.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Serverless Computing Function-as-a-Service (FaaS) Cloud Computing Performance Analysis Security Analysis

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

As Unmanned Aerial Vehicle (UAV) technology advances, UAVs are becoming more and more common in both military and civilian applications. The term flying ad hoc networks (FANET) is frequently used to describe multi-UAV networks. UAV clustering is a crucial path for UAV network applications since it may enhance network scalability, minimize energy consumption, and maximize network lifetime when multiple UAVs are divided into clusters for management. Additionally, the special features of these systems make it difficult to improve their defences against constantly changing security threats, making security provision in these systems especially complex. We introduced Secure and Hybrid Bio Inspired Optimization (SHBIO) for FANETs, an innovative, effective, and hybrid bioinspired algorithm, in this suggested framework. This research proposes an adaptable, secure, and efficient bio-inspired routing model with the goal of developing a new, trustworthy security framework. For this, it suggests Ant Colony Optimization (ACO), one of the most popular methods for trusted route computing. safe route selection using the ACO method. Among the interrelated parts and layers that comprise the architecture is the Trust Management System, which assesses each drone's reliability based on a variety of trust factors

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Jamming Attack, Gradient Monitoring, Communication Security, Multi-Agent Systems

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Accidents caused by fatigue are a serious problem, particularly in sectors like manufacturing and transportation. This work suggests a deep learning-based method for face recognition-based driver drowsiness detection and accident prevention. Driver fatigue is a major cause of road accidents, making real-time detection crucial for ensuring safety. Traditional methods like K-Nearest Neighbors (KNN) classify fatigue based on facial features but struggle with real-time tracking and temporal dependencies. To overcome these limitations, this project introduces a CNN + LSTM-based fatigue detection system that not only extracts facial features automatically but also analyzes fatigue patterns over time for improved accuracy. The system employs a Convolutional Neural Network (CNN) for feature extraction from facial images and a Long Short-Term Memory (LSTM) network to analyze temporal patterns associated with fatigue indicators such as eye closure. The proposed model processes real-time video frames, detects fatigue symptoms, and triggers alerts to prevent drowsy driving. The system is designed to be efficient and scalable, making it suitable for real-world deployment in vehicles and industrial safety applications. Experimental results demonstrate high accuracy in fatigue detection, showcasing the effectiveness of combining CNN and LSTM for robust facial-based fatigue analysis.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Driver Fatigue Detection, Convolutional Neural Network, Long Short-Term Memory, Real-Time Monitoring.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The current demand for skincare products and treatments has significantly risen. There is a growing fascination among individuals to enhance their appearance. Consequently, a variety of products have been launched to promote a youthful and attractive look. Serums have emerged as a key component in establishing an effective skincare routine. They come in a variety of formulations suitable for different skin types, including oily, dry, and everything in between. In this study, we examine a face serum suitable for all skin types. The primary component of the serum is sericin, known for its antityrosinase, anti-oxidant, hydration and anti-aging properties. Additional ingredients include chamomile extract, hyaluronic acid, and vitamin E. Hyaluronic acid is a crucial element in cosmeceuticals due to its hydrating and anti-aging benefits. Vitamin E has demonstrated significant antioxidant and moisturizing benefits for the skin, offering protection against UVB radiation damage. Chamomile essential oils are widely utilized in the fields of cosmetics and aromatherapy. Currently, there is no existing treatment that can effectively slow the aging of the skin. However, serums containing a blend of concentrated vitamins and acids have demonstrated remarkable results. The face serum was assessed for its physicochemical properties, including pH, viscosity, antimicrobial activity etc. The increasing focus on skincare indicates a societal change that places greater importance on individual appearance and beauty ideals.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Face serum, sericin, antityrosinase, anti-oxidant, anti-aging, hyaluronic acid, chamomile.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Aquatic macrophytes, often referred to as hydrophytes, encompass a wide range of macroscopic plants that thrive either fully or partially in water-based ecosystems. However, their populations are significantly impacted by factors such as eutrophication, sewage discharge, and industrial contaminants. Moreover, seasonal changes can lead to a marked reduction in the diversity of these aquatic plants. Consequently, it is essential to establish baseline data to assess these effects and maintain the health of aquatic ecosystems. A thorough survey was carried out to evaluate the presence of emergent macrophyte populations in the waterways of the study region, with careful documentation of the findings. The results indicate that the Jalna district is home to a rich variety of emergent macrophytes, with a total of 89 species identified. The district is particularly notable for its substantial representation of the Cyperaceae family, which comprises 35 species. Following this, the Poaceae family includes 8 species, while the Nymphaeaceae family has 5 species, and the Typhaceae family contains 4 species. Additionally, the Convolvulaceae and Graminaeae families each feature 3 species, and the Acanthaceae, Alismataceae, Amaranthaceae, Commelinaceae, Fabaceae, Plantaginaceae, and Polygonaceae families each have 2 species. Furthermore, one species was recorded from each of the following families: Apiaceae, Aponogetonaceae, Asteraceae, Boraginaceae, Brassicaceae, Cannaceae, Euphorbiaceae, Iridaceae, Juncaceae, Lythraceae, Marsileaceae, Pontederiaceae, Scrophulariaceae, Taccaceae, and Verbenaceae

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Aquatic plants, Lake Management, Wetlands, Emergent-Submerged-Floating macrophytes, Diversity, Water resources.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract-- Fire outbreaks are a common issue worldwide, causing significant damage to nature and human life. Modern fire detection solutions prioritize vision-based approaches over legacy sensor systems, enabling expansive monitoring and rapid threat identification in diverse environments. However, the detection process using image processing techniques can be complex and time- consuming. This paper proposes a Fire and Motion Detection System that utilizes Convolutional Neural Networks (CNNs) for high- accuracy fire detection. The system is trained on a dataset comprising 3,696 fire images and 541 non-fire images, totaling 4,237. Of these, 2,857 images were used for training and 1,921 images for testing. The CNN model employs convolution, activation functions, and max pooling operations. Through experimentation with different batch sizes and epoch values, the model achieved an accuracy of 94%, correctly predicting 1,817 out of 1,921 test images. Additionally, the system incorporates motion detection to address human-animal conflicts in agricultural fields. Using background subtraction and object classification (via YOLO or similar models), the system detects and classifies intruders (e.g., animals or humans) and sends real-time alerts to farm owners and officials via Telegram notifications. This study also reviews various smoke and fire detection techniques, including RGB and HSI models, to minimize false alarms and enhance early detection. The integration of fire and motion detection into a unified system provides a comprehensive solution for safeguarding agricultural fields and preventing disasters.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fire Detection Convolutional Neural Networks (CNN) Vision-Based Surveillance Image Processing Motion Detection Human-Animal Conflict Smart Agriculture YOLO Object Detection Real-Time Alerts Telegram Notification System Background Subtraction RGB and HSI Models Wildfire Monitoring Deep Learning for Fire Detection Precision Agriculture Forest Fire Prevention Animal Intrusion Detection Integrated Safety Systems AI in Agriculture Environmental Monitoring

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This research paper investigates the impact of salary disparity on employee performance and motivation in public and private sectors within the Surat district of Gujarat. Through primary data collection from employees across both sectors, the study analyzes how salary differences contribute to variations in performance, job satisfaction, and motivation. This paper also discusses how non-monetary incentives influence employees' attitudes and behavior and recommends policies to minimize negative impacts of salary disparity.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Salary disparity, employee performance, motivation, public sector, private sector, Surat district, Gujarat.

  License

Creative Commons Attribution 4.0 and The Open Definition