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.

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Services provided by public libraries in Maharashtra

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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.

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challenges, strategies, Nagaland, TVET.

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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.

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

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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.

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

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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

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

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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.

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

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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.

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

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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

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

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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.

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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

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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.

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

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Effective therapy of Parkinson's disease (PD), a progressive neurodegenerative disease that affects both motor and non-motor abilities, depends on an early and precise diagnosis. This study investigates a hybrid strategy for reliable PD diagnosis in humans that blends deep learning and machine learning models. Because of its layered structure, ResNet can extract high-dimensional, complicated features that are crucial for identifying minor patterns linked to Parkinson's disease.

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Parkinson's disease (PD), magnetic resonance imaging (MRI), pre-trained ResNet-18, support vector machine.

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Arishta means the fatal signs and symptoms which denotes imminent death. The detailed description of these Arishtas is found split into 12 chapters of Indriya Sthana of Charak Samhita. Arishtas definitely occur in diseased person before death [1]. This concept of Ayurveda is unique in itself and can help to assess the estimation of survival time and prognosis both at the same time. Indriya Sthana consists of 12 chapter, out of which the tenth chapter is discussed in this article. The 10th chapter deals with the Arishtas which indicate death within 3 to 7 days of time [2]. Hence, an in-detailed study of this chapter could help to determine the specific quality and probable survival time along with the prognosis of the disease.

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Arishta, death, sensory organs, prognosis, diseases, etc.

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Divulging a strong undercurrent of environmental ethics, the animal stories of Dhan Gopal Mukerji serve as the early source for ecological awareness. Dhan Gopal Mukerji was an early twentieth century Indian-American writer often remembered for his contribution to children's literature. His works build a cultural bridge between the East and West. Mukerji's childhood experiences in the wilderness of Indian jungle subtly influence his narratives which are derived from the Vedantic perspectives of ahimsa (non-violence) and interconnectedness among all forms of life. Mirroring deep ecology, his philosophy sees humans as part of a larger web of life and not as superior to it. Mukerji's portrayal of animals and nature align with eco-centric environmental concerns where all living beings are considered valuable in themselves, not just in relation to human use. Mukerji's works highlight the trauma faced by animals due to human conflicts criticizing anthropocentricism. Though Mukerji may not be explicitly categorized as an environmental activist but a close reading of his works reveals how living in harmony with nature was a major concern in his writings dedicated to children. He undoubtedly was the pioneer of nature writing even before the genre became popular.

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Eco-literature, Animal empathy, Harmony, Eastern philosophy, Coexistence, Environmental ethics, Spiritual Oneness

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This review attempts to present studies that are directly or indirectly relevant to the concepts of need and anxiety. The information included is drawn from both primary and secondary sources. Every effort has been made to incorporate pertinent literature that has a direct bearing on the subject.

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desire, construct, dissatisfaction, biologically, environments, encompass fundamental

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The GST (Goods and services tax was introduced on 1st July, 2017 as a historic step in the trajectory of advancements in indirect taxation system in India as it was meant to increase revenue productivity in India by widening the eligible tax base, removing cascading effect of indirect taxes and putting an end to multifarious and complex indirect tax system in India and replace it with one single indirect tax applicable across the nation. This research studies the impact of the implementation of GST on the long-term growth and development and employment generation in MSMEs in Textile Sector in Northern Delhi; in places like Karol Bagh, Rohini, Gandhi Nagar, Chandni Chowk and Samaypur Badli. By employing graphical analysis tools like Pie charts and qualitative analysis based on data and subjective comments in the survey, the study aims to provide a holistic view on the problems faced by MSME owners and benefits enjoyed by them due to developments in the GST system, like boost in export competitiveness and removal of cascading effect. The research also makes use of secondary qualitative data from government reports and case studies available online. Inferences from the research suggest that several creeping problems like disruptions in supply chain, fluctuation in price of raw material, excessive compliance costs and delays in receiving input tax credit still continue to haunt MSMEs while the benefits of it are also enjoyed by them.

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Textile, Supply chain, logistics, Goods and Services Tax (GST), inverted Duty structure

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Aim and objectives: To assess the efficacy of synbiotic product among selected PCOS (Polycystic ovarian syndrome) adult women from the age group of 20-40 years. Methodology: A Quantitative Approach, the True experimental research design was adopted to assess the effficacy of synbiotic product among PCOS (Polycystic ovarian syndrome)adult women in Kavitha Fertility Hospital, Coimbatore who fulfilled the inclusion criteria. A sample of 50 adult women from the age group of 20-40 years with PCOS was selected, from which 10 women were assigned to an experimental and control group, with 5 participants in each group. Both groups had a pretest to assess the clinical manifestations of PCOS. The experimental group then received a Synbiotic product supplementation for a period of 30 days, while the control group did not receive any supplementation. Following the 30th-day supplementation period, a post-test was conducted to evaluate the clinical manifestations of PCOS in both groups. The experimental group and control group were had a pretest and post-test assessments of ovarian volume by Transvaginal ultrasound scan Results: The study findings revealed that the post-test clinical manifestation unpaired 't' value for BMI was p=0.031, for waist-hip ratio was p=0.013, and for ovarian volume p=0.006 levels of clinical manifestations indicates a high statistical significance at p< 0.05 among PCOS adult women from the age group of 20-40 years. Conclusion: The results revealed that the synbiotic Product was effective in alleviating the clinical manifestations among PCOS adult women from the age group 20-40 years.

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synbiotic product, clinical manifestations, PCOS

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A comparative study to assess the knowledge and attitude on prevention and management of tuberculosis among the population in selected urban and rural area of district Fatehabad.In this study the urban population knowledge was adequate in only 4% of the participant where as in rural population it was adequate in only 0% of the participant. in urban population the attitude was found to be good for 56% and in rural population it was 45%.study concludes that the general population should be sensitized with the knowledge of tuberculosis and its management to enhance their understanding and to have a better attitude.

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comparative, Assess, Association, knowledge ,Attitude , Population ,Tuberculosis,Urban, Rural.

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Skin cancer refers to the abnormal growth of skin cells, typically triggered by DNA damage from exposure to ultraviolet (UV) radiation, leading to uncontrolled cell division and the formation of malignant tumors. Common signs of skin cancer include changes in the size, shape, color, or texture of moles or lesions, as well as the development of new growths or sores that do not heal. Early detection of skin cancer is crucial for successful treatment and improved prognosis. However, traditional methods of skin cancer diagnosis are often subjective, time-consuming, and reliant on expert interpretation, leading to challenges in accessibility and accuracy. In recent years, advances in image processing and machine learning have offered promising avenues for improving skin cancer detection through automated analysis of dermatoscopic images. It proposed the development and implementation of a novel skin cancer detection system utilizing convolutional neural networks (CNNs) for automated lesion classification. The system integrates features for data preprocessing, feature extraction, CNN model training, and diagnostic output visualization. Leveraging a diverse dataset of dermatoscopic images, the CNN model demonstrates high accuracy and robust performance in distinguishing between benign and malignant lesions.

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Parkinson's Disease (PD), Magnetic Resonance Imaging (MRI), Pre-trained ResNet-18, Support Vector Machine, Fuzzy Support Vector Machine.

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This paper explores the ethical and moral values embedded in the short stories of classical Sanskrit literature. By analyzing texts such as the Panchatantra, Hitopadesha, and Jataka tales, this study aims to uncover the philosophical ideals and moral teachings that these stories present. These tales, often written for both entertainment and instruction, reflect the cultural values of ancient India and continue to provide timeless insights into ethics, morality, and human behavior.

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Ethical Values, Short stories, Pancatantra, Hitopodesha

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A song recommendation machine is designed to provide personalized musical recommendations based on person options, helping people discover new collections of melodies tailored to their tastes. By taking advantage of the higher algorithms, the Gadget improves the general listening and simplifies the exploration of the melodies. As the melody performs an important function in the day -to -day life, Want's advice structures for sensitive transmission is more exceptional than ever. This framework carries detailed methodologies, equipment and implementations to guarantee adaptability and precision. It gives an uninterrupted and interactive person who delights, dynamically thinking of variables beyond listening discs. By promoting the effective interaction of the human computer, the system offers precise and custom -made recommendations, saving time and enriching the musical discovery for customers.

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Chatbot, song recommendation, Spotify API, Last.FM API, generation of reproduction lists.

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