Volume 14 | Issue 4

 Abstract

Agriculture remains the backbone of India's economy, yet farmers continue to face challenges such as limited access to expert guidance, language barriers, excessive use of chemical inputs, and unreliable internet connectivity. AgroLingua: AI-Powered Multilingual Farming Assistant addresses these issues by integrating artificial intelligence, IoT sensors, computer vision, and natural language processing. The system provides real-time insights on soil health, crop suitability, pest and disease detection, weather conditions, yield expectations, and market trends. With its voice-enabled interface supporting Telugu, Hindi, and English, AgroLingua ensures inclusivity and accessibility, even for farmers with low literacy levels. Its offline-first architecture further supports rural areas with inconsistent connectivity, while the platform's organic advisory module promotes sustainable and eco-friendly farming practices. The methodology behind AgroLingua follows a structured and modular approach that combines data collection, machine learning, and intelligent advisory generation. IoT sensors capture soil moisture, temperature, pH, and nutrient levels, while computer vision analyzes crop images to detect pests and diseases. The collected data undergoes preprocessing and feature extraction before being processed by rule-based and machine-learning-ready prediction modules. The system then generates personalized recommendations based on soil conditions, predicted crops, and regional context. A multilingual NLP layer enables voice-based queries and responses, and offline caching ensures uninterrupted use. This end-to-end pipeline ensures accurate predictions, localized insights, and scalable deployment, making AgroLingua a reliable and farmer-friendly decision support system.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence (AI), Natural Language Processing (NLP), Multilingual Systems, Precision Agriculture, Voice-Based Interaction, Intelligent Advisory Systems, Real-Time Query Processing

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The technology sector is characterized by high-velocity Mergers and Acquisitions (M&A), where the realization of synergistic value is highly contingent upon the seamless Post-Merger Integration (PMI) of financial systems. Traditional PMI literature heavily favors cultural and strategic alignment, often marginalizing the deep technical and mathematical complexities of financial data synchronization. This paper proposes a rigorous quantitative framework for integrating disparate accounting architectures. By utilizing vector space modeling for Chart of Accounts (CoA) harmonization, defining a composite Data Quality Index (DQI), and applying machine learning algorithms for entity resolution, this research provides a deterministic approach to preserving financial data integrity. We model the algorithmic complexities of large-scale Extract, Transform, Load (ETL) processes unique to high-transaction-volume technology firms, ultimately offering a scalable blueprint to mitigate regulatory (SOX) and operational risks during system convergence.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data Quality, MDG

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This review presents a comprehensive analysis of the formulation and evaluation of a cold cream containing Tagetes erecta extract

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Marigold cold cream, formulation, skin healing properties

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's digital era, excessive smartphone usage has become a major factor influencing individual productivity, focus, and overall well-being. While existing applications provide basic screen-time statistics, they fail to deliver meaningful insights or predictive analysis regarding user productivity. This paper presents an AI-powered Smartphone Usage Analytics and Productivity Prediction System that leverages real-world usage data combined with behavioral factors such as sleep patterns, stress levels, and focus time. The system utilizes a deep learning model to classify productivity levels into Low, Medium, and High categories and also generates a quantitative productivity score. By integrating machine learning with data visualization and database systems, the proposed solution provides personalized insights and actionable recommendations to users. The system is implemented as a web-based application using Streamlit, ensuring accessibility and ease of use. Experimental analysis demonstrates that combining behavioral attributes with usage patterns significantly improves prediction accuracy, enabling users to make informed decisions that enhance productivity.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smartphone Usage Analysis, Productivity Prediction, Deep Learning, Behavioral Analytics, Machine Learning, Streamlit, Data Visualization, User Behavior Modeling, AI-based Recommendation System

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: The contemporary student job search is deeply hindered by opaque Applicant Tracking Systems (ATS) that frequently reject candidates without providing actionable feedback. To resolve this structural inef- ficiency, we developed an AI-powered career navigation platform that transcends standard job boards. The proposed system features an automated resume analyzer utilizing Natural Language Processing (NLP), com- pletely eliminating manual data entry and reducing candidate onboarding time by 82%. We employ a hybrid recommendation engine that calculates transparent, explainable match scores, ensuring users understand the specific semantic variables driving their suggestions. Furthermore, the platform integrates an interactive skill gap dashboard paired dynamically with targeted educational course recommendations. During an 8-week beta deployment processing over 15,000 resumes, the system achieved an 87.3% matching precision--a 107% improvement over legacy ATS keyword scanners. Crucially, 76% of candidates actively engaged with the recommended skill-gap courses, leading to a 41% increase in subsequent interview shortlisting rates. By aggregating real-time market trends and actively mitigating algorithmic bias, our system drastically reduces job-search fatigue and provides highly actionable pathways for continuous professional development

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Machine Learning, Resume Parsing, Explainable AI, Recommendation System, Skill Gap Anal- ysis, Career Guidance

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The AI-Powered Stock Market Insight Application is an intelligent Android-based solution developed to help users understand stock market behavior, technical indicators, and short-term price movements more effectively. Although digital trading platforms have made stock market access easier, many retail investors still struggle to analyze live market data, interpret candlestick charts, and make informed trading decisions due to volatility, data complexity, and limited expert support. To address this issue, the proposed system combines real-time stock data processing, machine learning-based short-term prediction, interactive chart visualization, and AI-assisted guidance within a single mobile application. The application is developed using Java/XML for the frontend and Firebase Realtime Database for secure real-time synchronization and storage. It offers features such as live stock updates, trend analysis, candlestick chart interpretation, forecasting support, and an NLP-based chatbot that answers user queries and explains trading concepts in a simple and user-friendly manner. By integrating financial analytics with mobile accessibility, the system reduces the gap between complex market data and practical user understanding. The application aims to support both beginner and intermediate investors in making smarter, data-driven, and more confident investment decisions

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI-Powered Stock Market Insight, Stock Market Prediction, Machine Learning, Android Application, Firebase Real-time Database, Candlestick Chart Analysis, NLP Chatbot, Real-Time Data Analytics, Financial Forecasting, Technical Indicators

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper examines the role of Large Language Models (LLMs) in English language teaching through the theoretical lens of Bakhtinian dialogism. Bakhtin's ideas of heteroglossia, polyphony, and dialogic interaction highlight that meaning emerges through the interplay of diverse voices. While the traditional classroom already embodies this multiplicity through teacher-student exchanges and peer dialogue, the arrival of LLMs introduces a new interlocutor, artificial yet dialogically responsive, into the pedagogical arena. LLMs can simulate a wide range of registers, perspectives, and critical positions, creating opportunities for students to engage with multiple "voices" simultaneously. For instance, an LLM may provide feedback as a formalist critic, a peer reviewer, and a language tutor, compelling learners to evaluate, synthesise, and position themselves within a plurality of perspectives. In literature classrooms, LLMs can animate characters or critics, expand interpretive possibilities, and foster a genuinely polyphonic environment. The study employs autoethnography to examine the researchers with LLMs as learners, teachers, and critics. Reflective journaling of AI-human exchanges provides the basis for analysis, capturing both the machine's textual utterances and the researcher's responses. These narratives are read thematically through Bakhtin's framework to explore moments of dialogic expansion where LLMs simulate polyphony by generating multiple voices or perspectives, as well as tensions where the machine's lack of ethical answerability disrupts authentic dialogue. The paper argues that LLMs, when integrated critically, can cultivate dialogic competence, rhetorical agility, and AI literacy, thereby extending Bakhtinian dialogism into the digital age without displacing the ethical centrality of human pedagogy.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Index Terms: LLM, Bhakthin, Interlocuter, AI, and polyphony.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT: Background of the study: The IHI developed the "Ventilator Bundle," comprising four evidence-based practices, along with a methodology for implementation and compliance measurement. The study objectives to evaluate nursing officers' knowledge and practices related to ventilator-associated pneumonia (VAP) care. Research methodology: It employs a descriptive quantitative design with a sample of 100 participants selected through non-probability convenient sampling. The research tool consists of three parts: Part 1 covers socio-demographic information, Part 2 is a self-structured questionnaire with 24 items scored from 0 to 1, and Part 3 is a checklist containing 20 items, also scored from 0 to 1.conclusion: A study on ventilator-associated pneumonia (VAP) revealed that 67% of participants had excellent knowledge, 28% good knowledge, and 5% average knowledge. In terms of practices, 55% exhibited good practices, while 40% showed excellent practices, with no participants falling below fair practice levels. Overall, nursing officers implement appropriate VAP care practices.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords: knowledge, practice, ventilator-associated pneumonia (VAP),bundle of care, nursing officers.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Electricity theft is one of the most significant problems faced by power distribution companies, leading to substantial financial losses, reduced efficiency, voltage instability, and overloading of distribution networks. Unauthorized tapping, illegal connections, and meter bypassing not only affect revenue generation but also compromise system reliability and public safety. To address this issue, an efficient, low-cost, and automated monitoring solution is required.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Arduino Uno / Microcontroller GSM Module (SIM800 / SIM900) Power Theft Detection Smart Energy Meter Embedded System Electrical Monitoring System

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract The world has witnessed a commendable new media revolution, expansion of knowledge, and interactive communication. The new media have created virtual communities that have crossed geographical boundaries. Digital, networkable, compressible, and interactive are the basic characteristics of new media technologies. The Internet, in particular, offers the potential for a democratic postmodern public sphere in which citizens can engage in well-informed and non-hierarchical debate about their social structures. India has also made commendable progress in communication science and technology. Policymakers have recognized that active participation of underprivileged, marginalized, underserved, and under-represented segments of society, including women and vulnerable groups, is critical for inclusive development. As society shifts towards a knowledge-based and development-oriented society, the critical role of new media in Dalit empowerment becomes clear. The importance of the media in national development is widely acknowledged by media scholars.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

New Media, Inclusive Development, Empowerment of Dalits.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In the digital era, data security has become a critical concern due to the exponential growth of data and the increasing sophistication of cyber threats. Traditional centralized systems are often vulnerable to data breaches, unauthorized access, and single points of failure. Blockchain technology has emerged as a promising solution to address these challenges by providing a decentralized, transparent, and tamper-resistant framework for data management. This research paper explores how blockchain technology enhances data security by leveraging cryptographic techniques, distributed consensus mechanisms, and immutable data structures. The study also discusses applications, benefits, limitations, and future directions of blockchain-based security systems.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Blockchain, Data Security, Cryptography, Decentralization, Immutability, Consensus Mechanisms, Distributed Ledger Technology (DLT).

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Facial Emotion Detection is an important application of computer vision and deep learning that enables machines to recognize human emotions from facial expressions. This paper presents an efficient real-time facial emotion detection system using the ResNet-18 deep convolutional neural network architecture trained on the Extended Cohn-Kanade (CK+) dataset. The proposed system performs face detection using OpenCV Haar Cascade and applies preprocessing techniques such as resizing, normalization, and grayscale conversion before feature extraction. The ResNet-18 model automatically learns discriminative facial features and classifies expressions into seven emotion categories: happy, sad, angry, fear, surprise, disgust, and neutral. The system is capable of predicting emotions from live webcam input with high accuracy and confidence levels. Experimental results demonstrate reliable performance in real-time environments, making the system suitable for applications such as human-computer interaction, smart classrooms, healthcare monitoring, and driver assistance systems. The proposed approach improves classification efficiency while maintaining computational simplicity for practical deployment.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Facial Emotion Detection, Deep Learning, ResNet-18, Computer Vision, CK+ Dataset, Emotion Classification, OpenCV, Convolutional Neural Networks, Human-Computer Interaction, Real-Time Emotion Recognition

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's fast-changing digital economy, Small and Medium Enterprises (SMEs) are increasingly using digital marketing techniques to improve their market presence, customer engagement, and business performance. The different digital marketing tools and techniques used by SMEs, such as social media marketing, search engine optimization (SEO), email marketing, content marketing, and online advertising. The study also investigates the level of awareness, usage, and effectiveness of these digital marketing practices in achieving organizational goals. The study uses both primary and secondary data. The primary data was collected using structured questionnaires among SME owners and marketing managers, while secondary data was collected from journals, reports, websites, and previous studies. Statistical methods such as percentage analysis, graphs, and descriptive analysis were employed to analyze the data. The results show that digital marketing is an important factor in improving brand awareness, customer reach, and sales performance of SMEs. However, factors such as a lack of technical expertise, budget constraints, and limited digital infrastructure are some of the challenges that impede effective implementation. The study concludes that with proper training, planning, and cost-effective digital marketing tools, SMEs can effectively use digital marketing to create a competitive advantage and ensure sustainable growth.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Digital Marketing, Small and Medium Enterprises (SMEs), Social Media Marketing, Business Performance, Customer Engagement.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Shiksha Me Hindu Studies Hindu Adhyayan Ki Avashyakta Aur Iska Mahatv

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Shiksha Me Hindu Studies Hindu Adhyayan Ki Avashyakta Aur Iska Mahatv

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project presents the tribological behavior of silicon oxide (20 nm), ZDDP, and hBN nanoparticle additives in castor vegetable oil to enhance the lubricating performance. The nanoparticles were dispersed in the base oil at different concentrations (0.3%, 0.4%, and 0.6%). The prepared nano-lubricants were evaluated for their physical and tribological properties, including viscosity (using a Redwood viscometer), viscosity index, flash point, fire point, and pour point. The results indicate that the addition of nanoparticles significantly improves lubrication performance by reducing friction coefficient and wear. Surface analysis using scanning electron microscopy (SEM) confirmed the formation of protective films on the worn surfaces, which contributed to improved anti-wear characteristics.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Friction coefficient, lubricating oil, nanoparticles, wear behavior, SEM analysis

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Emotional Intelligence (EI) is defined as a type of social intelligence that involves the ability to monitor one's own and others emotions, to discriminate among them and to use the information to guide one's thinking and actions. (Mayer & Salovey, 1993). The present study was conducted to evaluate the effect of perceived maternal parenting styles on emotional intelligence among high school students. The sample consists of 100 B.Ed., students 50 male and 50 female students from five B.Ed colleges in Tirupathur district of Tamilnadu. Trait Emotional Intelligence Questionnaire ASF by Petrides et al. (2006) was used to measure emotional intelligence. To measure perceived maternal parenting style, Parenting Scale (P Scale) by Bharadwaj et al. (1998) was used. The parenting styles Rejection vs. Acceptance, Carelessness vs. Protection and Freedom vs. Discipline were taken for the present study. The data was analyzed using one-way ANOVA. It was found that perceived maternal parenting styles such as Rejection vs. Acceptance and Freedom vs. Discipline had a significant influence on emotional intelligence among the sample but the parenting style Carelessness Vs. Protection had no significant influence on the emotional intelligence among the sample. It was also found that the parenting style Rejection vs. Acceptance had a significant influence on emotional intelligence only among the males.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Emotional Intelligence, Perceived Maternal Parenting Styles.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Harmful algal blooms (HAB) pose increasing threat to coastal areas with climate change and global warming intensifying their impact. The aquatic ecosystem is one among the most severely affected specifically marine life. Aquaculture is increasingly vulnerable to the consequences of HAB's. This proposal introduces a Bayesian decision model for assessing harmful algal bloom (HAB) risk in aquatic systems under climate-driven warming, enriched with a Viveka (discernment) which is inspired by Shanti Parva from Mahabharata. Beyond standard probabilistic updating, the model includes a meta-judgment module that adjusts evidence based on its reliability, context, and consistency. This enables refined, wise decision outputs like warnings. This paper elaborates the model's structure, assumptions, and decision logic, without performing experimental regulation.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

HAB, Viveka, Bayes, Algal Blooms

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Career maturity is the level of awareness over various careers, desired attitude towards careers or work and competence in career understanding. It plays a crucial role in the vocational life individuals. Choosing the right career according to the skills set and aptitude of the students is very vital for career advancement. This study is a survey and experimental based study aims to find out the level of career maturity among higher secondary student in Puducherry and developing an interventional career awareness program for the students to foster career maturity among students. A sample of 320 higher secondary students is surveyed for their career maturity and 40 students were employed in pre-test post-test single group experimental design with and two session interventional program on career awareness. Findings of this study reveals that level of career maturity among higher secondary student is average with need for creating awareness. Gender, year of study and type of school have influence over career maturity and stream of study doesn't influence over career maturity among higher secondary students. Pre- test post-test interventional design indicate that their increase in awareness about various careers and its nature after the students exposed to two hours session. This study concludes that there is need for career awareness programs in higher secondary schools in Puducherry as the level of career maturity is average. Strategies to develop career maturity among higher secondary students is discussed.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Career maturity, higher secondary school students, career maturity fostering strategies

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The implementation of the proposed real-time measurement system integrates advanced machine learning, sensor data processing, and an interactive mobile user interface to deliver an efficient and accurate measurement solution. The system is built upon a pre-trained YOLOv5 object detection model, with the flexibility for custom training using datasets such as COCO to improve detection accuracy for domain-specific applications. Careful tuning of training parameters and evaluation using metrics like precision, recall, F1-score, and mean average precision (mAP) ensures reliable model performance. To enable real-time execution on mobile devices, the model undergoes optimization techniques including quantization, pruning, and hardware acceleration, significantly reducing computational complexity while maintaining accuracy. The integration of smartphone sensors, particularly the accelerometer, allows continuous real-time capture of device orientation data, which is processed and synchronized with the camera feed to support accurate depth estimation. The system also features a well-designed user interface that overlays detection results and measurement outputs directly onto the live camera view. Real-time visualization of object dimensions, along with user-controlled inputs such as device height, enhances usability and measurement precision. Overall, the implementation ensures low latency, high responsiveness, and a seamless user experience, making the system robust and suitable for real-world mobile application.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Real-time measurement, object detection, YOLOv5, machine learning, mobile application, sensor integration, accelerometer data, depth estimation, model optimization, quantization, computer vision, real-time processing, user interface, bounding box detection, and mean average precision (mAP).

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Enhancing convective heat transfer while maintaining an acceptable pressure drop is a critical requirement in compact heat exchanger design. In this study, an air-side passive enhancement technique is examined using sinusoidal fins integrated with surface dimples through a comparative CFD analysis of three configurations: plain, elliptical dimpled, and circular dimpled fins. The geometries are created in SolidWorks and simulated in ANSYS Fluent under steady-state turbulent flow conditions for inlet velocities ranging from 1 to 2.5 m/s. The results indicate that the addition of dimples significantly improves heat transfer performance compared to the plain fin. Among the tested configurations, the circular dimple exhibits the highest enhancement of about 18-20%, while the elliptical dimple shows an improvement of approximately 16%. This enhancement is mainly due to increased turbulence intensity, improved fluid mixing, and disruption of the thermal boundary layer. The Nusselt number also increases for both dimpled cases, confirming the improvement in convective heat transfer. However, this benefit is accompanied by an increase in pressure drop, where the elliptical dimple results in a higher rise of about 10.6%, while the circular dimple shows a relatively lower increase of 7-8%. Overall, the circular dimpled sinusoidal fin provides a better balance between heat transfer enhancement and pressure loss, making it more suitable for compact heat exchanger applications.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sinusoidal fin, dimpled surface, elliptical dimple, circular dimple, heat transfer enhancement, Nusselt number, pressure drop.

  License

Creative Commons Attribution 4.0 and The Open Definition