Volume 14 | Issue 5 |

 Abstract

Attendance management within academic institutions has historically relied on passive recording mechanisms that merely capture presence and absence without extracting deeper insights or enabling proactive decision making. The proposed Smart Attendance Prediction and Alert System introduces a comprehensive analytical layer on top of conventional tracking by examining the dynamics of total classes conducted, classes attended, absence frequency, and recurring behavioral tendencies such as selective absenteeism and clustered bunk patterns. By synthesizing historical trajectories with current progression, the system estimates the probability of a student falling below institutional thresholds and surfaces this risk early enough for meaningful intervention. The design assumes conceptual integration with institutional ERP platforms through secure API mediated data exchange so that attendance streams are ingested automatically and processed continuously. The output is not limited to a percentage but expands into interpretable risk categories accompanied by contextual explanations and recommended corrective actions. A dual notification mechanism communicates these insights to both the student and the parent, thereby strengthening accountability loops and reducing information asymmetry. In effect, the system repositions attendance from a retrospective metric into a forward looking signal that can influence behavior, improve consistency, and minimize last minute academic penalties.

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 Keywords

Attendance, Prediction, Alert, Analysis, API, ERP.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present device is indigenously prepared for all healthcare practitioners to support manufacturing in India. Additionally, it can be used in other sectors where there is a danger that contaminated air may cause respiratory disorders. Healthcare workers (HCWs) are at particular risk during pandemics and epidemics of highly virulent diseases with significant morbidity and a case fatality rate. These diseases include severe acute respiratory syndrome coronaviruses, SARS- CoV-1 and SARS-CoV-2, Middle Eastern Respiratory Syndrome (MERS), and Ebola. With the current (SARS-CoV-2) global pandemic, it is critical to delineate appropriate contextual respiratory protection for HCWs. All locally available components can easily be serviced and replaced, making it a cheaper device than all other Powered air-purifying respirators (PAPRs) available. The major components are the helmet and filter casing. There is moderate quality evidence for PAPR. Its use is associated with higher thermotolerance but lower mobility and communication ability scores. There has been a trend toward improved self-reported comfort with PAPR technology in low-quality observational simulation studies. Due to its two-layer filtering layers, it can be used in adversely contaminated environments. Field observational studies have shown no difference in infections among healthcare workers using the PAPR device compared to other matched ventilators. The PAPR was confirmed to have low mobility and high thermostability with audibility. However, more practical research is needed to explain the effectiveness of PAPR technology and provider satisfaction.

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 Keywords

Covid-19, PAPR, Respiratory Protection, Healthcare worker

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present study titled "Impact Study on Tamil Nadu Chief Minister Breakfast Scheme" aims to examine the effectiveness of the breakfast scheme introduced by the Government of Tamil Nadu in improving the nutritional status, school attendance, and academic performance of primary school children. The scheme was launched to address classroom hunger and enhance student participation in government schools. This study adopts a descriptive research design to analyze the impact of the scheme among beneficiaries in Coimbatore District. A total of 60 respondents including students, parents, and teachers were selected using convenient sampling method. Primary data were collected through structured questionnaires and interviews, while secondary data were gathered from journals, books, and government reports. The findings reveal that the scheme has significantly improved students' attendance, punctuality, energy levels, and concentration in classrooms. It also reduced the financial burden on parents and improved the nutritional intake of children. However, certain challenges such as need for menu variety and limited community participation were observed. The study concludes that the Chief Minister Breakfast Scheme is a highly effective social welfare initiative contributing to child development and educational outcomes. It recommends strengthening awareness, improving food variety, and enhancing monitoring mechanisms for better implementation.

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 Keywords

Impact study, Tamil Nadu scheme, Chief Minister Breakfast scheme

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid spread of misinformation and fake news through online social networks has become a major societal concern, leading to political instability, social conflicts, and financial fraud. This project aims to develop a defensive machine learning model that can effectively detect and mitigate fake news propagation. The proposed system employs Natural Language Processing (NLP) techniques to analyze textual features and classify news articles as real or fake. Additionally, graph-based analysis is used to examine user behavior and detect bot accounts that contribute to the spread of misinformation. The methodology involves data collection from reliable fake news datasets (e.g., Fake Newsnet, LIAR, and Kaggle Fake News datasets), text preprocessing using TF-IDF and Word Embeddings, and classification using machine learning algorithms such as Logistic Regression, Random Forest, and LSTM (Long Short-Term Memory networks). Furthermore, network analysis using Graph Neural Networks (GNNs) and Network helps identify suspicious user activity and misinformation propagation patterns.

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 Keywords

defensive machine learning model ,Natural Language Processing,graph-based analysis ,-IDF and Word Embeddings.journalism integrity

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In this paper, we introduce fractional integrals and differentials of the extended Mittag-Leffler functions E_(?,?)^(?,? ;c,d) (z;p,q). In this continuation of the study of fractional calculus.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fractional Intergral, Mittag-Leffler Function, Extended Mittag-Leffler Functions

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Fixed point theory in metric spaces using interpolative contractive mapping has greatly developed in recent times. In this article we prove fixed point results satisfying interpolative type integral contractive condition in metric spaces.

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 Keywords

Metric space, integral type contractive condition, integral type interpolative contraction conditions, fixed point.

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This paper examines the issues, expenses, and administrative strains encountered by businesses in the process of meeting the India Goods and Services Tax (GST). It dwells upon the problems of the layered tax system, the constant shifts in taxation, and the inconsistencies in regulations implemented in different states, which also impacts SMEs with few resources, specifically. The administrative burden, such as a large amount of paperwork, several returns filing, and the adherence to the regional differences are examined. The paper also looks at the efforts by the government to make the life of GST easier, including easy filing of returns, GST help desks and online training programs. It also puts focus on technology, such as ERP software and artificial intelligence-based applications that are capable of automating compliance. Suggestions on how to lessen the compliance burden are given as well as policy recommendations on how to simplify the processes. Lastly, the research directions in the future are also defined with the emphasis on industry-specific issues and geographic differences in the GST implementation processes that will help improve compliance and assist businesses.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

GST compliance, administrative burden, SMEs, GSTN portal, digital transformation, tax filing simplification, government initiatives.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence (AI) has emerged as a powerful technology in transforming space exploration and satellite imagery analysis by enabling efficient processing of large and complex geospatial data. With the rapid growth of high-resolution satellite imagery, traditional data analysis methods are no longer sufficient to provide accurate and timely insights. AI techniques such as machine learning and deep learning, particularly Convolutional Neural Networks (CNNs), have significantly improved image classification, object detection, and segmentation tasks. Advanced approaches, including transformer-based models and multimodal AI systems, further enhance data interpretation by integrating satellite imagery with environmental and sensor data. Recent innovations such as edge AI enable real-time onboard satellite processing, reducing latency and improving efficiency, while reinforcement learning supports autonomous spacecraft navigation and mission optimization. Generative AI techniques are also utilized for image enhancement and data reconstruction. These advancements have expanded applications in climate monitoring, disaster management, precision agriculture, urban planning, and deep space exploration. However, challenges such as data quality issues, high computational requirements, limited labelled datasets, and hardware constraints in space environments remain significant. Future research directions, including federated learning, swarm intelligence, and AI-driven interplanetary exploration, aim to address these limitations. Overall, the integration of AI technologies is transforming satellite imagery analysis and space systems into more intelligent, autonomous, and efficient frameworks, paving the way for next-generation innovations in Earth observation and beyond.

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 Keywords

Artificial Intelligence, Satellite Imagery, Space Exploration, Machine Learning, Deep Learning, Convolutional Neural Networks (CNN), Transformers, Edge AI, Reinforcement Learning, Generative AI, Remote Sensing, Geo AI, Earth Observation, Autonomous Systems, Multimodal AI

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Creative Commons Attribution 4.0 and The Open Definition

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In recent decades, growing awareness about nutrition, fitness, and disease prevention has led to an increased emphasis on healthy eating practices. Social media platforms, wellness movements, and health-focused lifestyle trends have significantly influenced individuals' attitudes toward food and dietary habits. While adopting a balanced and nutritious diet is generally associated with improved physical and psychological well-being, an excessive and rigid preoccupation with consuming only foods perceived as healthy may lead to problematic eating patterns. One such emerging phenomenon in the field of eating behavior research is orthorexia nervosa, a term introduced by Steven Bratman to describe an unhealthy obsession with eating foods considered pure, natural, or healthy. Orthorexia nervosa is characterized by an intense fixation on the quality and purity of food rather than its quantity. Individuals displaying orthorexic tendencies often develop strict dietary rules, eliminate entire food groups perceived as unhealthy, and experience significant anxiety or guilt when these self-imposed dietary standards are violated. Over time, this rigid adherence to dietary ideals may lead to nutritional deficiencies, psychological distress, and social impairment, particularly when eating behaviors interfere with daily functioning or social interactions. Contemporary psychological perspectives suggest that orthorexic tendencies may be closely linked with dietary obsessions and rigid beliefs about health and nutrition. Individuals may develop strong cognitive beliefs that consuming only certain types of foods leads to moral superiority, improved self-control, or optimal health outcomes. These beliefs may gradually reinforce restrictive eating behaviors and contribute to obsessive patterns of food selection, meal preparation, and dietary monitoring. Furthermore, increasing exposure to health-related information through digital media and wellness culture may contribute to the internalization of unrealistic standards regarding "clean eating" and dietary purity. While healthy eating behaviors are widely encouraged, excessive preoccupation with food quality and health beliefs may paradoxically result in maladaptive patterns resembling eating disorder symptomatology. Despite growing research interest in orthorexia nervosa, the psychological mechanisms underlying orthorexic tendencies remain insufficiently explored. In particular, limited research has examined how dietary obsessions and beliefs about healthy eating contribute to the development and maintenance of orthorexic behaviors. Understanding these underlying cognitive and behavioral patterns is important for identifying individuals at risk and for informing prevention and intervention strategies. Therefore, the present study aims to examine orthorexic tendencies among individuals and explore their relationship with dietary obsessions and healthy eating beliefs, contributing to the expanding body of literature on emerging eating-related psychopathology.

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 Keywords

orthorexia nervosa, perfectionism, obessions, dietary habits

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study focuses on analyzing the business development strategies and tools used for client acquisition with reference to Kirtane and Pandit LLP, Chartered Accountants. Client acquisition plays a significant role in the growth of professional service firms by improving market reach, competitiveness, and client relationships. The study covers key business development approaches such as referrals, networking, digital marketing, and relationship management, which strongly influence client acquisition in chartered accountancy firms. It examines how these strategies impact client growth, service delivery, and overall firm performance. Various analytical tools such as questionnaire surveys, percentage analysis, and chart representation are used to evaluate the effectiveness of client acquisition practices. The study also highlights the role of business development activities in strengthening client trust and long-term relationships. It identifies both opportunities and challenges associated with acquiring new clients. The findings provide insights into improving business development practices for sustainable growth. Overall, the study emphasizes the importance of effective strategies and tools in enhancing competitiveness and supporting long-term success.

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 Keywords

study emphasizes the importance of effective strategies and tools in enhancing competitiveness and suppor

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Creative Commons Attribution 4.0 and The Open Definition