Volume 14 | Issue 5

 Abstract

This paper presents Edumetron, a smart student productivity and academic management mobile application designed to enhance learning efficiency, track academic performance, and provide instant doubt resolution using artificial intelligence. The application integrates multiple functionalities including productivity tracking, AI-based doubt solving, analytics visualization, and gamification features such as XP and streak systems to motivate consistent learning behavior. Edumetron is developed using Flutter for cross-platform mobile development, Firebase for authentication and database management, and a Python Flask backend for AI-based query processing. The system allows students to manage their academic tasks, monitor performance metrics, and receive instant responses to their doubts through an AI-powered chatbot interface. The application is designed with a user-friendly interface and follows modern mobile application development standards. By combining productivity tools with AI capabilities, Edumetron provides a centralized and intelligent academic support system. The platform demonstrates a practical implementation of integrating mobile development with artificial intelligence to solve real-world educational challenges.

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 Keywords

Edumetron, Student Productivity, AI, Flutter, Firebase, Analytics, Gamification

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Creative Commons Attribution 4.0 and The Open Definition

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Balancing authenticity and innovation in traditional interior design reflects the evolving relationship between heritage and modern creativity. Traditional elements, rich in cultural history and craftsmanship, hold symbolic and aesthetic value but must adapt to contemporary lifestyles, sustainability, and preferences. Interior designers navigate this by reinterpreting motifs, materials, and techniques within modern frameworks, preserving cultural significance while ensuring functionality. Key strategies include sustainable practices, leveraging digital technologies to enhance craftsmanship, and creating culturally resonant yet practical interiors. This ensures traditional elements remain dynamic and relevant, harmonizing cultural heritage with modern design demands and environmental considerations.

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Authenticity, Innovation, Cultural heritage, Contemporary design, Sustainability, Conservation, art restoration

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Creative Commons Attribution 4.0 and The Open Definition

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In recent years, prolonged screen usage and sedentary lifestyles have significantly increased the prevalence of poor posture, leading to various health issues such as back pain, neck strain, and reduced productivity. This project presents a comprehensive smart posture monitoring system that integrates Internet of Things (IoT) technology with real-time computer vision and machine learning techniques to address this problem effectively.The system utilizes a personal computer equipped with a webcam to continuously monitor the user's posture. Using advanced computer vision frameworks such as OpenCV and MediaPipe, key human body landmarks are extracted and analyzed in real time. These extracted features are then processed using a machine learning model based on the K-Nearest Neighbors (KNN) algorithm, which classifies posture into categories such as "Good" and "Bad." The trained model ensures accurate and efficient posture detection under various conditions.In addition to posture analysis, the system incorporates physiological monitoring through a MAX30100 pulse oximeter sensor connected to an Arduino Nano. This sensor measures vital parameters such as heart rate and blood oxygen saturation (SpO?), providing additional insights into the user's health condition. The collected sensor data is transmitted to an ESP32 microcontroller, which acts as a communication bridge and sends the data to the cloud using the Blynk platform. The ESP32 also displays real-time data on an I2C LCD screen for local monitoring.When improper posture is detected, the system immediately triggers multiple alert mechanisms to ensure user awareness and corrective action. These include an audio alert generated using text-to-speech, an email notification with an annotated image of the detected posture, and a signal sent to the microcontroller for visual indication. The integration of these features ensures a robust and responsive feedback system.Overall, the proposed system provides a low-cost, non-invasive, and intelligent solution for continuous posture monitoring. By combining IoT, machine learning, and computer vision, it enhances user awareness and promotes healthier sitting habits. The system is highly scalable and can be further extended for applications in workplaces, educational institutions, healthcare monitoring, and smart environments.

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 Keywords

Index: Smart Posture Monitoring, Internet of Things (IoT), Computer Vision, OpenCV, MediaPipe, Machine Learning, K-Nearest Neighbors (KNN), ESP32, Arduino Nano, MAX30100, Blynk, Real-Time Monitoring, Posture Detection, Health Monitoring System, Webcam-Based Analysis

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Fashion has always been changing but after social media it has changed a lot faster than before. Platforms like Instagram and TikTok made fashion more visible and easy to follow. Earlier only designers and big brands used to decide trends but now anyone can start a trend. This paper is about how social media changed fashion, how people shop and how brands work now. It also talks about both good and bad effects like creativity and also fast fashion problem.

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Social media, fashion trends, influencers, fast fashion, consumer behavior, digital platforms, personal style, online marketing, sustainability, fashion industry

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This study examines transformational trends in Dagbon traditional dress codes from 1800 to 2024, focusing on historical progression, material change, and symbolic continuity. It investigates how Dagbon clothing practices evolved across pre-colonial, colonial, post-colonial, and contemporary periods while retaining core cultural meanings. A qualitative descriptive design was employed, with data collected through semi-structured interviews with 33 participants, comprising 12 elders, 8 artisans and traditional tailors, and 15 young adults in contemporary fashion, complemented by field observation, photographic documentation, and archival sources. Thematic content analysis identified patterns across historical phases. Findings reveal that early nineteenth-century attire consisted of minimal coverings from animal hides and plant fibers. From the late nineteenth century, structured garments including kpalayincho, piito, amoosi, smocks, and handwoven cotton wrappers emerged, reflecting technological advancement and social differentiation. The twentieth century reinforced ceremonial symbolism and hierarchical expression through fugu and inner smocks. In the twenty-first century, traditional garments increasingly merge with modern tailoring and global fashion influences. The study concludes that Dagbon dress demonstrates adaptive continuity, functioning as both material cultures shaped by economic change and a symbolic system sustaining identity and social meaning.

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Dagbon, traditional dress, clothing transformation, material culture, symbolic meaning

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT In today's rapidly evolving business environment, service quality has emerged as a critical factor influencing customer satisfaction and operational efficiency. With increasing competition and rising customer expectations, organizations are required to deliver fast, reliable, and high-quality services. Recent industry reports indicate that the global average customer satisfaction score is approximately 78%, highlighting the growing importance of service quality in shaping customer perceptions. This study examines the impact of service quality on customer satisfaction and operational efficiency in the service sector. In today's highly competitive environment, organizations are required to deliver high-quality services to meet increasing customer expectations and maintain a competitive advantage. The main objective of this research is to analyze how different dimensions of service quality influence customer satisfaction and how these factors contribute to improving operational efficiency. The study is based on primary data collected from 40 respondents using a structured questionnaire. A quantitative approach has been adopted, and the data has been analyzed using simple statistical tools such as percentage analysis and graphical representation. The findings of the study indicate that there is a strong positive relationship between service quality and customer satisfaction. It has been observed that factors such as staff behavior, responsiveness, reliability, and use of technology significantly influence customer perception. Furthermore, the results show that improved service quality leads to enhanced operational efficiency by reducing waiting time and improving service delivery processes. However, certain areas such as delay in services and communication gaps still require improvement. The study concludes that organizations should focus on continuous improvement in service quality and adopt modern technologies to enhance both customer satisfaction and operational efficiency. This research provides useful insights for managers and organizations aiming to improve their service performance and achieve long-term success. In addition to the core findings, the study also emphasizes the growing importance of customer-centric strategies in modern organizations. It highlights that businesses which actively monitor customer feedback and adapt their service processes accordingly are more likely to achieve higher satisfaction levels. The role of continuous improvement and innovation in service delivery has also been identified as a critical factor in sustaining operational efficiency. Moreover, the study underlines the need for organizations to invest in employee training and digital transformation to enhance service performance. These insights make the research relevant for both academic purposes and practical implementation in real-world business environments. Furthermore, the study brings attention to the dynamic nature of customer expectations, which continue to evolve with advancements in technology and increased market competition. It suggests that organizations need to regularly evaluate their service quality standards and align them with changing customer needs. The findings also indicate that even minor improvements in service delivery, such as reducing response time and improving communication, can significantly enhance customer satisfaction levels. In this context, the study reinforces the idea that operational efficiency is not only about cost reduction but also about delivering consistent and high-quality customer experiences. These observations contribute to a better understanding of how service-oriented organizations can achieve sustainable growth. Furthermore, current data suggests that 86% of customers are willing to pay more for better service experiences, emphasizing the direct link between service quality and business performance. The study also highlights that improved service quality leads to enhanced operational efficiency by reducing delays and improving service delivery processes. Additionally, research shows that 88% of customers are more likely to repurchase after a positive service experience, while a significant number may switch brands after repeated poor experiences. Overall, the study concludes that maintaining high service quality is essential for improving customer satisfaction and achieving operational excellence. Organizations must adopt customer-centric strategies, invest in technology, and continuously improve their service processes to remain competitive and ensure long-term growth.

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Keywords: Service Quality, Customer Satisfaction, Operational Efficiency, Service Sector, Customer Experience

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 Abstract

Representation of Friedrich Nietzsche’s Übermensch in Matt Reeves’ The Batman

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Representation of Friedrich Nietzsche’s Übermensch in Matt Reeves’ The Batman

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A Self-Adaptive Tri-Band Thermal Reconfigurable Microstrip Patch Antenna Is Proposed For Wireless And Defence Communication Applications. The Antenna Is Designed On An FR-4 Substrate With A Circular Slot Structure To Achieve Multiband Operation Within The 1-5 Ghz Frequency Range. The Proposed Antenna Resonates At 1.98 Ghz, 4.3 Ghz, And 4.8 Ghz With Satisfactory Return Loss And Acceptable VSWR Characteristics. The Thermal Reconfiguration Technique Improves Impedance Matching And Adaptive Performance Under Varying Conditions. Simulation Results Obtained Using CST Studio Suite Confirm Stable Radiation Characteristics, Good Gain, And Efficient Multiband Performance, Making The Antenna Suitable For Modern Adaptive Wireless Communication Systems.

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Microstrip Patch Antenna, Thermal Reconfiguration, Tri-Band Antenna, Circular Slot Antenna, Wireless Communication, Defence Applications, CST Studio Suite, Adaptive Antenna

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

"PREVALENCE OF ANXIETY AND DEPRESSION AMONG ASTHMA PATIENTS IN LATUR CITY."

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"PREVALENCE OF ANXIETY AND DEPRESSION AMONG ASTHMA PATIENTS IN LATUR CITY."

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We know that to achieve goals we should require sufficient fund i.e., finance. The Prime Minister of India in Cop-26 climate summit announced that India will attain net zero emissions by 2070. In order to meet these climate targets, countries like India will need approximately USD 1trillion in additional financing over the next ten years. Here, it is clear that India has need to extra finance to achieve above desired goals. Such needed extra finance known as GREEN FINANCE. Green Finance is to increase the level of financial flow from banking (micro credit, insurance and investments), from the public private and NPOs sector to sustainable development priorities.

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Green Finance , Climate change, Sustainable Development, Green Investment, Green Bonds, Green Initiatives.

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Remote Sensing, GIS, Land Use and Land Cover, Sub-Watershed, Agrani River Basin

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Creative Commons Attribution 4.0 and The Open Definition

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Cryptocurrency markets are characterized by significant fragmentation, leading to frequent price discrepancies across exchanges. These inefficiencies create opportunities for arbitrage trading, where traders exploit price differences to generate profits. However, identifying and executing profitable arbitrage strategies in cryptocurrency markets is challenging due to factors such as transaction fees, network congestion, and market volatility. This paper explores the use of multi-source data, including real-time exchange prices, blockchain transaction met-rics, and social media sentiment analysis, to identify and evaluate cryptocurrency arbitrage opportunities. By integrating these diverse data streams into a unified framework, we develop a robust methodology that leverages statistical models, machine learning algorithms, and graph theory to detect and execute arbitrage trades efficiently. Our approach incorporates probabilistic risk management techniques to account for uncertainties such as slippage and la-tency, ensuring the sustainability of arbitrage strategies. Backtesting results demonstrate the effectiveness of the proposed framework, achieving a profitability rate of 12.5% with a Sharpe ratio of 1.8 and a maximum drawdown of 5.2%. The findings highlight the importance of multi-source data integration in overcoming the challenges of cryptocurrency arbitrage and provide valuable insights for traders, researchers , and financial practitioners. This research contributes to the growing body of knowledge on cryptocurrency trading strategies and underscores the potential of advanced data analytics in unlocking new opportunities in decentralized financial ecosystems .

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ryptocurrency arbitrage Multi-exchange price analysis Market fragmentation Real-time data analytics Multi-source data integration Blockchain metrics Social media sentiment analysis

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In recent years, digital payment systems have changed the way people manage and use money, especially in developing countries like India. One of the most important digital payment innovations in India is the Unified Payments Interface (UPI). UPI allows people to transfer money instantly between bank accounts using smartphones, making financial transactions fast, secure, and easy. Because of this, UPI has become a very popular mode of payment for daily activities such as shopping, bill payments, and money transfers. The main aim of this research is to study how the use of UPI affects consumer financial behaviour. This study focuses on changes in spending habits, saving behaviour, and dependency on cash. It also compares how people from different age groups use UPI and how their financial behaviour differs after adopting digital payments. The study is based on a descriptive and analytical research design. Primary data was collected through a structured questionnaire shared using Google Forms. A total of 100 respondents from different age groups participated in the survey. The collected data was analysed using basic statistical tools such as percentage analysis and comparative analysis. The results of the study show that UPI usage has significantly increased the frequency of transactions and has reduced the use of cash. Many users reported increased spending, including impulse purchases, due to the ease of digital payments. The study also found that younger age groups are more comfortable with UPI and show stronger behavioural changes compared to older individuals. The research concludes that while UPI provides great convenience and improves financial accessibility, it may negatively affect spending discipline if not used carefully. The findings of this study can help policymakers, banks, and financial institutions design better awareness programs to promote responsible use of digital payment systems.

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Unified Payments Interface (UPI), Digital Payments, Consumer Financial Behaviour, Spending Behaviour, Impulse Buying, Age Cohorts, Financial Discipline,

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Creative Commons Attribution 4.0 and The Open Definition

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The increasing complexity of modern aircraft systems, coupled with the demand for higher operational efficiency and safety, has driven the evolution of maintenance strategies from reactive and preventive approaches toward predictive, data-driven methodologies. Traditional maintenance practices, which rely on scheduled inspections and failure-based interventions, often lead to unnecessary component replacements or unexpected system failures, resulting in increased operational costs and reduced aircraft availability. In this context, Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative technologies capable of leveraging large volumes of aircraft operational data to enable accurate prediction of system health and remaining useful life. This article presents a comprehensive data-driven framework for AI-based predictive maintenance in aircraft systems, integrating sensor data acquisition, health monitoring systems, and advanced analytics to detect anomalies, predict failures, and optimize maintenance scheduling. The study explores the application of machine learning techniques, including supervised learning, time-series analysis, and anomaly detection, to model complex system behavior across critical aircraft subsystems such as engines, avionics, and hydraulic systems. A scalable system architecture is outlined, encompassing onboard data collection, edge processing, secure data transmission, and cloud-based model training and deployment integrated with Maintenance, Repair, and Overhaul (MRO) operations. Furthermore, the article focuses key challenges associated with real-time deployment, including data quality, class imbalance due to rare failure events, model interpretability, and compliance with stringent aerospace certification standards. The operational benefits of predictive maintenance, including reduced unscheduled downtime, improved safety, and cost optimization, are critically examined. Finally, emerging research directions such as digital twin integration, federated learning across aircraft fleets, and explainable AI are discussed as pathways toward next-generation intelligent maintenance systems. By combining domain-specific knowledge with advanced AI methodologies, this article establishes a structured approach for implementing predictive maintenance solutions that enhance reliability, efficiency, and safety in modern aerospace operations.

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Artificial Intelligence, Predictive Maintenance, Aircraft Systems

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Creative Commons Attribution 4.0 and The Open Definition

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The evolution of e-commerce has significantly reshaped modern consumer behavior, offering unparalleled convenience and access to global marketplaces. However, a major drawback of traditional online shopping is the inability to perceive products in a real-world context, leading to uncertainty, misjudgment of size, placement issues, and frequent product returns. Augmented Reality (AR) offers a transformative solution by enabling customers to visualise products in their own environment through mobile devices. This study presents the development of an AR-based e commerce system that integrates optimised 3D product models, Firebase-based secure authentication, and Google Scene Viewer for AR visualisation. The methodology emphasises true-to-scale model creation, mobile-optimised rendering, gesture-based interaction, and cloud-linked product retrieval. The proposed system significantly enhances user clarity, improves product understanding, and increases purchase confidence. Test results demonstrate that AR visualisation can reduce product-related ambiguity and strengthen the overall shopping experience. In addition to furniture and home products, the system is extended to support virtual clothing try on and accessories visualisation, enabling users to preview apparel, glasses, watches, and jewellery on their own body using AR-based overlay techniques.

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--Augmented Reality, E-commerce, Google Scene Viewer, 3D Models, Firebase Authentication, Mobile AR.

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In the modern business environment, organizations are increasingly focusing on sustainability along with profitability. Growing environmental issues such as climate change, pollution, and resource depletion have encouraged companies to adopt eco-friendly practices. Green finance plays an important role by supporting investments in renewable energy, energy efficiency, and waste management. It helps organizations balance economic growth with environmental responsibility. This study examines the impact of green finance initiatives on sustainability and environmental responsibility in the corporate sector, with reference to Weikfield Foods Pvt. Ltd... The research focuses on practices such as solar energy adoption, resource conservation, and efficient operations However, challenges such as high initial cost and lack of awareness still exist. Overall, green finance proves to be an effective tool for sustainable development and long-term business growth.

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Green Finance, Sustainability, Environmental Responsibility, Renewable Energy Financial Performance.

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Creative Commons Attribution 4.0 and The Open Definition

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: Gond art is a significant tribal art form that originates from the Gond community in central India. Initially practiced as a ritualistic and decorative expression on walls and floors, it reflects the community's close relationship with nature, folklore, and spiritual beliefs. Over time, this art form has adapted to modern contexts, transitioning onto paper, canvas, and commercial platforms. This study examines how Gond art has evolved while maintaining its traditional identity. It explores the incorporation of new materials, changing themes, and the influence of contemporary markets. The paper also discusses the challenges of preserving authenticity in the face of modernization. Overall, the research highlights how Gond art continues to exist as both a cultural tradition and a dynamic form of contemporary expression.

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: Gond Art, Tribal Art, Contemporary Art, Traditional Art, Indian Folk Art, Cultural Heritage

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Creative Commons Attribution 4.0 and The Open Definition

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ABSTRACT BACKGROUND: Radiculopathy or nerve root pain arise from disc herniation, spinal stenosis radiating down the leg in a dermatomal pattern. This study focuses on disability, pain and range of motion of spine The study evaluates "The effectiveness of McKenzie technique versus Lumbar stabilization on reducing symptoms and disability of Lumbar radiculopathy. OBJECTIVE: The purpose of the study is to evaluate the effectiveness of McKenzie technique and Lumbar stabilization for the patients with Lumbar radiculopathy. METHODOLOGY: This study included 30patients, they were divided into Group A and Group B. Group A given McKenzie technique and Group B given Lumbar stabilization exercise. Pain was assessed using Visual analogue scale (VAS), Functional disability was measured using Oswestry disability index and Range of motion by Schober test. RESULT: The results between pre-treatment and post-treatment scores of pain and disability are considered. The mean and standard deviation are taken for both the Group A and Group B. The Group A showed better improvement in mean &standard deviation using Visual Analogue Scale, Oswestry disability index scores and Range of motion value than the Group B. CONCLUSION: Both groups showed better improvement in reducing pain and functional disability. This study proved that Group A showed better improvement in reducing pain and reducing functional disability when compared to Group B.

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KEYWORDS: Radiculopathy, McKenzie technique, chronic low back pain, Oswestry disability index, Lumbar stabilization exercise, Visual analogue scale

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Creative Commons Attribution 4.0 and The Open Definition

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The Right to Information (RTI) Act, which came into force on October, 12th 2005 marked a historical step towards transparency and accountability in administration in India. Nearly, two decades, the Act has been instrumental in exposing corruption and various scams, empowering citizens to demand information from public authorities. However, while the Act has undoubtedly brought about remarkable change, certain amendments to the Right to Information rules are necessary to prevent misuse, streamline the process, and reduce the burden on the courts.

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The Right to Information Act - 2005, Constitution, Indian Parliament, The Central Information Commission, Transparency, Accountability, Good governance.

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Creative Commons Attribution 4.0 and The Open Definition

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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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Creative Commons Attribution 4.0 and The Open Definition

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

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Creative Commons Attribution 4.0 and The Open Definition