Volume 14 | Issue 3 |

 Abstract

Mobile phones are being increasingly used due to advances in digital device technology and the Internet. Learning on mobile phones has become one of the most popular and useful tools for students of all ages worldwide. But any new technology also has shortcomings that should be addressed promptly and effectively to reduce its side effects. A multi-pronged approach can be used to reduce the ill effects of mobile phones. The introduction of mobile technology has raised awareness among library professionals of the need to acquire technology and understand its main advantages. Developing digital information that is distinctly readable, understandable, and customisable to users' needs is a challenge for libraries.

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 Keywords

Mobile Apps, Mobile Applications, Library Automation

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Malda District is one of the important districts of West Bengal. It has its long history from the ancient period having many historical places and samples of historical architectural scriptures. In ancient times Malda was the capital of Bengal which is famous for the place of Gour, Adina. The history of Malda may be mentioned in the Ancient age, Middle age and Modern age. I have presented the era of history of the ages separately. I have summarized that Gourbhumi consists of Malda and Murshidabad of West Bengal. The important aspects of these ages are Pala dynasty, Sen Dynasty, Bangadesh, Pandrubardhan and Barendra etc. In the Middle age there were the dynasties like Khilgi dynasty, Balbani dynasty, Tughlag dynasty, liliyas Shahi dynasty and Mughal Period and Hindu dynasty. In the Modern age the British government used force on Farmers of Indigo (Neal). The peasant movement was held several times and it had a special role in the independence movement.

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Key-Words: Malda, Gour, History, Dynasty and Ancient etc.

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Information and Communication Technologies (ICTs) have profoundly reshaped every aspect of human life over the past few decades .ICT has revolutionized education by providing fresh opportunities for both teaching and learning. ICT refers to the technologies that facilitate access to information through telecommunications. The present study had investigated The Effect of ICT on Academic Achievement of History Student in high Secondary School.The major objectives of this study was to know the differences in achievement of History due to use of ICT and other traditional method from the gender perspectives (Boys & Girls) and Location Perspectives (Urban & Rural).Only sixty (60) students were selected randomly from the higher secondary standard school participated in the study. In this study the Present research investigator had followed the "pre-experimental design (Two groups, static design)". The study found that there is significant effect of ICT on the academic achievement of the students all W.B.C.H.S.E under High Secondary School students for class-XI of Nadia district. For data analysis descriptive statistics (Mean, Median, & S.D) and under inferential statistics t-test will be used. In the 21st century, Information and Communication Technology (ICT) has become an integral part of daily life, influencing various aspects, including education. Achievement in the School subjects is a way for adult to maintain their personal worth; there must be a strong drive for achievement, Academic achievement can also performs the willingness to achieve skill and ability of the students with the help of ICT.

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 Keywords

Academic achievement, ICT, Higher Secondary School, School students

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Inhabiting the strategically significant north-western frontier of the Indian subcontinent, Afghans maintained continuous contact with and influence in South Asia. This paper examines their relationship with one of the most powerful imperial formations in the region, the Mughal Empire. Mughal-Afghan interactions began with the defeat of the Afghan Lodi dynasty at the foundation of Mughal rule and continued through to the later years of the empire, during which Afghan presence in the political affairs of Delhi remained significant. Drawing upon both historical accounts and Pashto literary sources, including the works of contemporary Pashtun poet Khushal Khattak, this paper argues that Afghan-Mughal relations cannot be understood as uniformly antagonistic or cooperative. Rather, they were characterized by a complex interplay of resistance, accommodation, and cultural expression, also varying with the social and aristocratic positioning of the individuals, reflecting the dynamic nature of frontier politics and identity in early modern South Asia.

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Afghan- Mughal Relations, Pashto, Khushal Khattak, Pashtun, Frontier

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Indian deaf and hard-of-hearing (DHH) children are exposed to severe psychomotor, cognitive, and socio-emotional disabilities because of deficits in auditory perception and systemic educational disabilities. Studies have shown that there are impairments in the processing of the vestibular, balance, and rhythmic synchronization of this population. This paper discusses Rabindra Nritya, a holistic dance tradition by Rabindranath Tagore, as an interdisciplinary intervention of psychomotor development. Rabindra Nritya focuses on natural expressiveness, flowing hasta mudras, and visual-gestural communication, and as such, it harmonizes with the visual-gestural and sensory capabilities of DHH learners. The study is based on embodied cognition and neuroscience, and how cross-modal plasticity enables deaf children to use visual and tactile senses to play with rhythm, which boosts executive functions and their spatial awareness. The paper is a review of evidence of Dance-Movement Therapy (DMT) supporting movement-based learning as an emotional regulation and social integration learning method. In turn, we suggest the Nritya-Bodh (Movement-Cognition) Model, which is a theoretical basis that combines the notions of kinesthetic anchoring, multi-sensory rhythmic integration, narrative-gestural mediation, communal co-regulation, and cultural rootedness. This model intersects movement and cognition, making Rabindra Nritya a cultural art not just of cultural art but also as a therapeutic pedagogical practice. This methodology has provided a culturally-relevant and culturally-specific strategy to facilitate motor and cognitive development in Indian DHH children and establish inclusion via special education, a vital gap in special education.

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 Keywords

Rabindra Nritya, deaf education, psychomotor development, dance-movement therapy, embodied cognition, inclusive education, Tagore pedagogy, special education in India, hearing impairment, Sangit Bhavana

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Forest fires are a major environmental threat causing severe damage to ecosystems, wildlife, and human life. Early detection is essential to minimize losses and improve response time. This project proposes an IoT-based forest fire detection system using LoRa communication for long-range and low-power monitoring. Multiple sensors such as temperature, humidity, smoke, and flame sensors are used to continuously monitor environmental conditions. The collected data is processed using a microcontroller to detect fire risks in real time. LoRa technology ensures reliable communication even in remote forest areas with limited network coverage. A GPS module is integrated to identify the exact location of fire incidents. Additionally, an AI-based model analyzes historical data to predict high-risk zones. The system is cost-effective, scalable, and improves early warning and disaster management efficiency.

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IoT, Forest Fire Detection, LoRa Communication, Environmental Monitoring, Temperature Sensor, Smoke Detection, GPS Tracking, Artificial Intelligence, Real-Time Monitoring, Alert System, Early Warning System.

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Plagiarism has become a significant concern in academic and content-driven environments due to the widespread availability of digital resources. Most existing plagiarism detection systems operate online and depend on cloud-based databases, raising issues related to data privacy, cost, and accessibility in low-connectivity environments. This paper presents an offline plagiarism detection system using machine learning techniques. The proposed system performs text preprocessing, feature extraction using TF-IDF, and similarity computation using cosine similarity to detect potential plagiarism within a locally maintained document repository. It generates similarity reports with percentage scores and highlights overlapping content for easy interpretation. Experimental evaluation demonstrates that the system effectively detects direct and partial plagiarism with acceptable accuracy in offline environments. The solution provides a privacy-preserving and cost-effective alternative suitable for educational institutions and organizations with limited internet access.

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Plagiarism Detection, Offline Systems, Machine Learning, TF-IDF, Cosine Similarity, Text Similarity, NLP

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Selecting an appropriate career path is a critical challenge for many students due to limited guidance, lack of self-awareness, and insufficient understanding of industry requirements. This work presents an Advanced Student Career Analysis and Prediction System that uses a data-driven approach to recommend suitable career options based on student attributes such as academic performance, technical skills, aptitude, and personality traits. The system is developed as a web-based application using Python and Flask, where a trained machine learning model analyzes input data and classifies students into relevant career domains like software development, data analysis, and management. The results demonstrate that the system effectively provides personalized career recommendations, helping students, institutions, and counselors make informed decisions and improving the overall efficiency of career guidance systems.

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- Machine Learning, Career Prediction System, Student Career Guidance, Educational Data Mining, Random Forest, Skill Analysis, Predictive Modeling, Web-Based Application

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Rapid urbanization, industrial expansion, and increasing water scarcity have intensified the demand for efficient and sustainable wastewater treatment technologies. Conventional treatment systems, while effective in removing bulk organic matter and suspended solids, face significant limitations in addressing emerging contaminants, nutrient overloads, and energy inefficiencies. Recent advancements in wastewater treatment focus on the integration of innovative physical, chemical, and biological processes to enhance treatment performance and resource recovery. Key developments include membrane-based technologies such as membrane bioreactors and nanomaterial-enhanced membranes, advanced oxidation processes for the degradation of recalcitrant pollutants, electrochemical treatment methods, and the application of artificial intelligence for process optimization and real-time monitoring. Additionally, sustainable approaches emphasizing circular economy principles--such as nutrient recovery, energy generation, and water reuse--are gaining prominence. This paper reviews recent technological advancements in wastewater treatment, evaluates their advantages and challenges, and discusses future research directions aimed at achieving environmentally sustainable and cost-effective wastewater management systems.

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Wastewater treatment advancements, membrane bioreactors, advanced oxidation processes, nanotechnology in wastewater treatment, electrochemical treatment, resource recovery, and artificial intelligence in wastewater management.

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Artificial Intelligence (AI) has emerged as a transformative force in Human Resource Management, particularly in talent acquisition processes. This study examines the role of AI in transforming recruitment practices, focusing on its effectiveness, potential bias, and ethical implications within the Indian organizational context. The study adopts a descriptive research approach and is based on primary data collected through structured questionnaires from HR professionals involved in talent acquisition. It explores the application of AI-driven tools such as resume screening systems, applicant tracking systems, predictive analytics, and recruitment chatbots, and evaluates their impact on efficiency, decision-making, and candidate selection processes. The findings indicate that AI significantly enhances recruitment efficiency by reducing time-to-hire, improving screening accuracy, and enabling data-driven decision-making. AI-based tools also contribute to better candidate-job matching and overall recruitment performance. However, the study also identifies critical concerns related to algorithmic bias, lack of transparency, and potential risks of discrimination due to biased training data. Furthermore, ethical challenges such as data privacy, accountability, and the need for human oversight were highlighted as key factors influencing the adoption of AI in recruitment. The study concludes that while AI offers substantial advantages in transforming talent acquisition, its successful implementation requires responsible usage, ethical governance, and a balanced integration of human judgment with technological capabilities.

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 Keywords

Artificial Intelligence, Talent Acquisition, Recruitment Automation, Algorithmic Bias, Ethical Implications, Human Resource Management, Data-Driven Decision Making, Recruitment Efficiency, Candidate Experience, India

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