Volume 13 | Issue 4 |

 Abstract

Artificial Intelligence has rapidly become an integral part our daily lives, transforming various aspects of society and opening up new possibilities and opportunities. However, the growth of AI also raises concerns about its impact on society and the potential consequences of its widespread adoption. This research paper provides a comprehensive overview of the impact of AI on varies aspects of society, including the economy, education, healthcare, employment, and ethics. To achieve this goal thorough review of existing research and data on the impact of AI was conducted. The literature review focused on the economic, social ,and ethical implications of AI ,as well as the challenges associated with its implementation .The review found that while AI has the potential to bring significant benefits to society ,it also poses challenges and risks that need to be addressed .The paper also presents a discussion of the impact of AI on different sectors of society ,including healthcare ,education, and employment .The analysis found that AI has the potential to improve patient outcomes and provide more efficient and effective healthcare services .It can also transform education by providing personalized and adaptive learning experiences .At the same time ,he implementation of AI in the workplace raises concerns about job displacement and the potential for economic inequality .In addition ,the paper evaluates the ethical implications of AI and identifies the need of responsible development and development of AI systems. This includes the need for ethical frameworks and guidelines to address issues such as bias, privacy, and transparency.Overall, this research paper provides a comprehensive overview of the impact of AI on various aspects of society by doing so, this paper helps to guide policy -makers, technology experts and the public towards the responsible and equitable development of AI.

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 Keywords

Artificial intelligence, Technology, Society, Innovations, Computers, Productivity, Machines.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The growing number of space debris threatens operational satellites and upcoming space missions significantly. Existing Space Situational Awareness (SSA) infrastructure is challenged in precisely tracking, predicting, and characterizing the debris environment, especially small, large numbers of objects. The challenges stem from sensor coverage gaps, the intricacy of orbital perturbations, data processing bottlenecks, and the inability to estimate object characteristics important for precise risk assessment. In this paper, the state-of-the-art in tracking space debris is comprehensively covered, highlighting the constraints of classic techniques and new emerging possibilities for Artificial Intelligence (AI) that can be improved through radar data analysis. The common usage of Kalman Filters and the extensive body of studies employing AI/ML algorithms such as LSTMs and CNNs for determining orbits, predictions, and characterization are reviewed by us. Principal areas of research lacuna were seen to include sparse application of deep learning into direct radar data streams, an absence of rigorous focus on real-time identification, and the demand for comprehensive and meaningful comparisons among AI and non-AI alternatives in realistic situations. This study establishes the precursor for next-generation SSA systems employing AI by recognizing imperative challenges and lucrative areas of research that collectively would lead toward enhancing the security and sustainability of space activities.

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 Keywords

Space Debris, Space Situational Awareness (SSA), Artificial Intelligence (AI), Machine Learning (ML), Radar Data Analysis, Orbit Determination, Trajectory Prediction, Kalman Filter, LSTM, CNN, Deep Learning, Space Surveillance and Tracking (SST)

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI, Crop prediction, Random Forest, Gradient boosting.

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Creative Commons Attribution 4.0 and The Open Definition

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Rehabilitation assistive devices are necessary for stroke patients, muscle trauma patients, or patients with age-related muscle atrophy. In this research, a 3D-printed upper limb assistive device was developed with simplicity, customization, and enhanced muscle rehabilitation in mind. With the use of FDM technology and biocompatible materials like PLA and TPU, the device provides light, ergonomic, and patient-specified support. Its modular design enables easy personalization, making it suitable for diverse therapy needs. Preliminary tests on physical therapy patients showed enhanced comfort, usability, and adherence to rehabilitation. The results highlight 3D printing's cost-effectiveness and potential for scalable application in clinical and home settings.

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 Keywords

Upper limb rehabilitation, 3D printing, Assistive device, FDM technology, PLA and TPU materials, Stroke recovery, Modular design, Patient-specific therapy

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Creative Commons Attribution 4.0 and The Open Definition

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The COVID-19 pandemic has significantly impacted research activities and publications across academic disciplines, including Library and Information Science (LIS). This study presents a bibliometric analysis of LIS research publications from India during the COVID-19 period, examining publication patterns, research trends, and scholarly collaboration. The analysis covers research articles published in peer-reviewed journals from March 2020 to December 2022. Using data extracted from major bibliographic databases, the study evaluates various parameters including publication volume, authorship patterns, institutional contributions, and thematic focus areas. Findings reveal a notable surge in digital library services, information literacy, and remote learning-related research during this period. The study identified key research clusters centered around digital transformation of libraries, information-seeking behavior during lockdowns, and emerging technologies in library services. Collaboration patterns show an increase in multi-institutional research partnerships, possibly facilitated by remote working conditions. The research output demonstrates the LIS community's rapid response to unprecedented challenges, with particular emphasis on technological adaptation and service innovation. This study contributes to understanding how the Indian LIS research landscape evolved during the pandemic, offering insights for future research directions and crisis preparedness in library and information services.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bibliometric, COVID-19, Library Science, Information Science, Research Output, India

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Creative Commons Attribution 4.0 and The Open Definition

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This is a well-established fact now that the avowed object of Ghosh as a writer has been to put to the centre stage the hitherto neglected facets of history. He in all his novels evinces his tenacious efforts to delineate such aspects of history as have been relegated to the margins in the traditional historiography. One such institution of the colonial past is the British army formed largely of Indians soldiers that have always been a little-discussed subject in the conventional history. Ghosh in The Glass Palace directs his attention to delineate the history of the British institution of the colonial army. His representation of the Indian British army is distinctive in so far as he seeks to underline the traumas and mental anguish of the Indian soldiers serving in the British army. There is no gainsaying the fact that the constitution and structure of the colonial army was racialized. Indian soldiers as subalterns had to bear racial discrimination at the hands of their white superiors or British counterparts that culminated in a sense of dissatisfaction and discontent amongst them. Ghosh here aims at projecting the inside view of the army and his portrayal of this colonial institution is unique in so far as he seeks to foreground the dilemmas and predicament of Indian soldiers. This paper seeks to present the ever-present discontent and ever-lurking dissent amongst the British Indian soldiers who suffered constant humiliation at the hands of their British superiors and counterparts. Their predicament was further aggravated by the sense of displacement, dislocation and rootlessness caused by the peculiar circumstances of their lives.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Alienation, Displacement, Subaltern, Dislocation, Migration, Dissent, Identity Crisis, Dilemma, Self-realization

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Creative Commons Attribution 4.0 and The Open Definition

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The classification of fruits is an essential task in agriculture, food processing, and retail industries, ensuring quality control and efficient sorting. Conventional methods depend on inspection, which is often slow, labor-intensive, and inconsistent. To address these limitations, this study employs Transfer Learning with pre-trained Convolutional Neural Network to develop an fruit classification system. In this research, deep learning models such as MobileNetV2 are fine-tuned to classify fruit images with high accuracy. The pre-trained networks are adapted to recognize different fruit categories by leveraging their feature extraction capabilities while significantly reducing training time. A Flask-based web application is developed to allow real-time classification, enabling user to upload fruit images and get instant predictions, making it ideal for real-time applications. The findings demonstrate that Transfer Learning is a highly effective approach for fruit classification, offering a scalable and reliable solution for automating the process. This system has potential applications in smart agriculture, automated food inspection, and digital marketplaces, enhancing efficiency and reducing human effort.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Transfer Learning, Convolutional Neural Networks, , MobileNetV2, Flask, Smart Agriculture.

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Creative Commons Attribution 4.0 and The Open Definition

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The proliferation of deceptive and computer-generated reviews constitutes a major challenge in e-commerce, social media, and digital marketing domains. To address this critical issue, the current work introduces an innovative ensemble-based methodology integrating linguistic analysis and reviewer behavioural profiling for accurate differentiation between authentic and fabricated textual reviews. Employing a diverse dataset comprising real and artificially generated reviews and using an ensemble of Logistic Regression, Random Forest, and Long Short-Term Memory (LSTM) networks collaboratively analyse linguistic patterns indicative of fraudulent textual review. Complementing textual analysis, a novel meta-feature engineering strategy assesses reviewer credibility through parameters such as review frequency, rating variance, and burst activity metrics. This meta-data-based approach simultaneously finds reviewer authenticity probabilities as new reviews are posted, indicating evolving behavioural patterns. The system computes an integrated probability score, effectively combining textual and meta-behavioural data. Overall evaluation demonstrates robust performance, effectively capturing emergent spam behaviours in real-time. The proposed methodology shows significant potential for practical deployment in automated moderation, digital content verification, and online fraud prevention applications.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fake review detection, Ensemble modelling, LSTM, Behavioural meta-analysis, Dynamic classification

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Creative Commons Attribution 4.0 and The Open Definition

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When fuel prices rise and environmental pollution turns into a crying need, hybrids have become an economically viable substitute for conventional gasoline cars. Hybrid technology combines electric motors and internal combustion engines to provide efficiency with low emissions. The present research effort tries to investigate the extent of awareness and satisfaction of hybrid car owners within the city of Coimbatore. It formulates the main determinant factors, disadvantages, and extent of increase in adoption by consumers.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hybrid Cars, Fuel Efficiency, Customer Satisfaction, Awareness, Green Mobility.

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Creative Commons Attribution 4.0 and The Open Definition

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The rapid growth of e-healthcare, fueled by IoT devices and wearables, has introduced significant privacy challenges, particularly in securing sensitive patient data collected and transmitted across distributed environments. To address these concerns, a novel Nomadic Agent System (NAS) architecture is proposed, combining edge computing, a central node with Kafka-based request management and ElasticSearch data indexing, and cloud storage. This architecture aims to enhance privacy protection by leveraging advanced technologies to secure data at multiple levels. A key innovation is the integration of Large Language Models (LLMs) within the nomadic agents at the central node, which are employed to improve data anonymization techniques. By utilizing LLMs, the system provides a more robust defense against re-identification attacks, ensuring that sensitive patient data is anonymized effectively while remaining usable for analysis and decision-making. The NAS architecture operates across multiple layers, with edge computing handling data collection and preprocessing, the central node managing data requests and indexing, and cloud storage ensuring scalable and secure data retention. The use of Kafka and ElasticSearch at the central node enables efficient data processing and retrieval, while the LLM-based anonymization process adds an additional layer of privacy protection. Potential benefits of this approach include enhanced data security, improved anonymization, and scalability for large-scale e-healthcare systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

E-healthcare, Privacy, Nomadic Agent, Edge Computing, Anonymization, Large Language Models, Kafka, ElasticSearch

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Creative Commons Attribution 4.0 and The Open Definition