Volume 14 | Issue 3

 Abstract

Career guidance and job recommendations have become increasingly complex due to the rapid evolution of industry skill requirements and the diversity of individual user profiles. Accurate identification of skill gaps and alignment between candidate capabilities and job market expectations is essential for improving employability outcomes. This paper presents PathFinder AI, an intelligent career guidance system that leverages Retrieval-Augmented Generation (RAG) to analyze resumes, recommend suitable job roles, and generate personalized learning paths. The system processes unstructured resume data to extract relevant skills and experience, which are then semantically compared with industry job descriptions using vector embeddings. A knowledge base containing curated job requirements and learning resources is employed to retrieve contextually relevant information through similarity-based search. The retrieved knowledge is integrated with a lightweight language model to generate explainable job recommendations and structured learning guidance. By combining semantic retrieval with controlled language generation, PathFinder AI improves the accuracy, relevance, and interpretability of career recommendations compared to traditional keyword-based systems.

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 Keywords

Retrieval-Augmented Generation (RAG), Career Guidance System, Resume Analysis, Skill Gap Analysis, Job Recommendation, Personalized Learning Path, Semantic Search, Vector Embeddings, Artificial Intelligence, Full-Stack Web Application.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Regional histories play a crucial role in decentralizing dominant historiographical narratives and highlighting the dynamic interplay between ecology, society, and political transformation. Purulia District, situated at the western frontier of West Bengal and historically associated with the Manbhum region, represents a distinctive cultural landscape shaped by environmental constraints, tribal resilience, religious plurality, colonial restructuring, and post-independence integration. Despite its historical significance, Purulia has often remained peripheral within mainstream Bengal historiography, which tends to privilege deltaic and urban-centered developments. This study critically examines the cultural heritage and historical evolution of Purulia from early historical periods to the contemporary era. Employing a qualitative historical-analytical methodology based on archival records, archaeological findings, anthropological accounts, and policy documents, the research situates Purulia within broader debates on regional historiography, subaltern agency, and intangible cultural heritage. The findings suggest that Purulia's socio-cultural identity evolved through processes of negotiation rather than passive assimilation. The district's tangible heritage--including temple architecture, sculptural remains, and settlement patterns--reflects trans-regional connectivity, while intangible traditions such as Chhau dance, Tusu, Bhadu, and Karam festivals demonstrate continuity within transformation. Colonial administrative interventions restructured agrarian relations and forest governance, yet indigenous frameworks of identity persisted. Post-independence linguistic reorganization and development policies further reshaped the district's political and cultural orientation. The study argues that Purulia should be understood as an active historical agent whose ecological setting and tribal foundations shaped a distinctive regional modernity. Recognizing its layered heritage contributes to broader discourses on cultural sustainability and decentralized historiography in India.

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 Keywords

Purulia; Regional Historiography; Tribal Society; Cultural Heritage; Chhau Dance; Colonial Transformation; Indigenous Identity; Eastern India.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In modern sports, data and artificial intelligence are widely used to improve player performance, predict injuries, and support strategic planning. However, many AI models are difficult to interpret because they do not clearly explain how their predictions are generated, which reduces trust among coaches and analysts. This research proposes an Explainable Artificial Intelligence (XAI)-based sports analytics system that integrates player performance analysis, injury risk prediction, and match outcome prediction within a unified framework. The system analyzes sports data, including player statistics, match history, and injury records, using machine learning techniques, while XAI methods are applied to clearly explain the reasoning behind each prediction. The results demonstrate that the proposed system provides accurate predictions along with meaningful explanations, thereby enhancing decision-making and increasing confidence in AI-based systems. Overall, the study highlights the importance of XAI in making sports analytics more transparent, reliable, and suitable for real-world applications.

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 Keywords

Explainable AI, Sports Analytics, Machine Learning, Injury Risk Prediction, Player Performance Analysis, Match Outcome, SHAP, Data Science

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

n the modern era, digitalization is transforming traditional sectors, including agriculture. Despite being the backbone of India's economy, agriculture still faces challenges such as limited access to quality resources, middlemen exploitation, and lack of real-time weather information. AgroPrime is a full-stack web application developed using the MERN (MongoDB, Express.js, React.js, Node.js) architecture to provide a smart digital solution for farmers. The platform offers an integrated e-commerce system for purchasing seeds, fertilizers, and agricultural equipment, along with a real-time weather forecasting module and an informational section covering pest control and government schemes. The system is designed with a responsive interface and multi-language support (English, Marathi, Hindi) to ensure accessibility for rural users. AgroPrime aims to bridge the gap between traditional farming practices and modern digital technology, improving efficiency, transparency, and productivity in agriculture

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

MERN Stack, Smart Agriculture, E-Commerce Platform, Real-Time Weather Forecasting, Digital Farming, MongoDB, React.js, Agricultural Technology

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The Gaze-Based Mouse Control System with Voice Assistant is designed to provide a hands-free and user-friendly way to interact with a computer without using a traditional mouse or keyboard. The system uses a standard webcam to track the user's eye movements and control the mouse cursor based on gaze direction, while eye blinks are used to perform mouse click actions. In addition to eye tracking, a voice assistant is integrated to recognize spoken commands for tasks such as opening applications, scrolling, typing, and executing system operations. Computer vision techniques are used for real-time face and eye detection, and speech recognition is employed to convert voice commands into actions. This approach is especially beneficial for physically challenged users and also supports touch-free computing for general users. The proposed system is low-cost, easy to use, and improves accessibility by offering a natural and intuitive human-computer interaction experience.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gaze-Based Mouse Control, Eye Tracking, Voice Assistant, Computer Vision, Speech Recognition, Human-Computer Interaction, Assistive Technology, Hands-Free Computing, Accessibility, Webcam-Based Interaction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

the observational study to assess Sthula Purusha Lakshana in overweight and obese individuals, has shown the classical features of Sthula Purusha Lakshana, as described in Ayurvedic texts, are observed with varying severity among overweight and obese individuals, as measured by the Body Adiposity Index (BAI).

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 Keywords

sthoulya, body adiposity index, overweight , obese

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial General Intelligence (AGI) represents the next stage in artificial intelligence, aiming to develop systems with human-like cognitive abilities such as reasoning, learning, adaptability, and autonomous decision making across multiple domains, in contrast to narrow AI designed for specific tasks. The rapid growth of the Internet of Things (IoT), with its vast network of interconnected sensors, devices, and cyber-physical systems, offers a rich environment for AGI by continuously generating large volumes of heterogeneous, real-time data that enhance contextual awareness and intelligent behavior. The integration of AGI into IoT infrastructures holds transformative potential for applications including smart cities, healthcare monitoring, industrial automation, autonomous transportation, and intelligent energy management, enabling systems to evolve from rule-based automation to self learning, predictive, and context-aware intelligence capable of operating in complex and dynamic environments. However, this convergence also introduces significant challenges such as computational scalability, energy efficiency, privacy and security risks, ethical concerns, and the difficulty of deploying robust, generalizable learning models on decentralized and resource-constrained IoT devices. Addressing these challenges through approaches like edge intelligence, federated learning, and hybrid cloud-edge architectures is essential to realizing the full potential of AGI-enabled IoT systems, which could ultimately redefine intelligent digital ecosystems by enabling autonomous, resilient, and human-like decision-making.

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 Keywords

Artificial General Intelligence (AGI), Internet of Things (IoT), Cognition-Driven Connectivity, Intelligent IoT Systems, AIoT, Edge Intelligence, Distributed Intelligence, Context-Aware Computing, Autonomous Decision-Making

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Creative Commons Attribution 4.0 and The Open Definition

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In Tamil Nadu, 55.4% of urban women workers are employed in the formal sector in regular wage or salaried jobs; around 32% of women employed in Chennai are often considered a proxy for formal sector employment; however, their participation in stock market investments continues to be significantly low. This study examines the level of financial autonomy, risk appetite, and investment portfolio of urban working women in Chennai. Using primary data of 100 respondents collected through a structured questionnaire, the study analyses the influence of demographic and socio-economic factors such as education, income, risk appetite and investment experience on women's investment decisions. Descriptive statistics, chi-square analysis, and graphical representations are employed to assess decision-making autonomy and risk behaviour. The findings indicate that higher levels of education and income enhance women's financial autonomy and confidence in investment decision-making. Nevertheless, most respondents prefer low-risk and secure investment instruments such as mutual funds, gold bonds, and government securities, while direct participation in equities and other high-risk assets remains limited. Persistent risk aversion, gaps in financial literacy, and social influences continue to constrain women's active involvement in the stock market. The research highlights the need for targeted financial literacy initiatives, women-centric investment advisory services, and supportive institutional frameworks to promote informed risk-taking and greater stock market participation among women. Key Words: In Tamil Nadu, 55.4% of urban women workers are employed in the formal sector in regular wage or salaried jobs; around 32% of women employed in Chennai are often considered a proxy for formal sector employment; however, their participation in stock market investments continues to be significantly low. This study examines the level of financial autonomy, risk appetite, and investment portfolio of urban working women in Chennai. Using primary data of 100 respondents collected through a structured questionnaire, the study analyses the influence of demographic and socio-economic factors such as education, income, risk appetite and investment experience on women's investment decisions. Descriptive statistics, chi-square analysis, and graphical representations are employed to assess decision-making autonomy and risk behaviour. The findings indicate that higher levels of education and income enhance women's financial autonomy and confidence in investment decision-making. Nevertheless, most respondents prefer low-risk and secure investment instruments such as mutual funds, gold bonds, and government securities, while direct participation in equities and other high-risk assets remains limited. Persistent risk aversion, gaps in financial literacy, and social influences continue to constrain women's active involvement in the stock market. The research highlights the need for targeted financial literacy initiatives, women-centric investment advisory services, and supportive institutional frameworks to promote informed risk-taking and greater stock market participation among women.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Financial Literacy, Autonomy, Investment Portfolio, Risk Appetite

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Creative Commons Attribution 4.0 and The Open Definition

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This paper examines evolving trends in household finance in Paschim Bardhaman district of West Bengal, focusing on income levels, savings behaviour, and expenditure patterns. Drawing on primary survey data and broader state-level socioeconomic statistics, the study documents the financial behaviour of households within the district and situates local patterns within broader Indian household finance trends. The analysis highlights the linkages between income levels, savings choices, and consumption behaviour, offering policy implications for financial inclusion and socioeconomic welfare.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Household finance, savings, expenditure, income distribution, Paschim Bardhaman, financial behaviour.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

?????????? ??? ??????? ????? ???? ????? ?????????? ?????????? ??? ????????? ????? ????. ?????, ?????, ???????, ????? ?????????? ???????????? ?????????? ????? ????. ?????????? ????? ????? ??? ??????????? ???? ???????????? ?????? ???? ???, ???? ?????????? ????? ??? ???????? ?? ???? ?????????? ????. ????? ???????????? ???????? ??????? ????????, ?????????? ????, ??????, ??.??.?????, ???? ??????, ?????????? ?????????? ?????? ??????? ??????. ??????????? ?????????????? ????? ???? ????, ????? ???????? ?????, ????? ?????, ?????? ?????? ????? ???? ???? ????. ?? ???????? ????? ???? ???? ????? ????? ?????? ????. ??????? ?????????? ?????????? ??????? ?????? ???? ??????????, ??? ??? ??????? ?? ??????? ??? ???????? ???????? ????. ????????? '? ???????' (2009) ?? ???????? ?????????? ??????????, ??????? ????????? ??? ????????? ???????? ???????? ???????? ?????????? ?????? ???. "???? ??????", "???? ??", ????????? ???????", "?? ???? ?????" ?? ????? ?????????? ???????????? ??????, ???????? ??? ?????????? ????? ????? ????? ??? ?????. ???? ????? ??????? ?????? ??????? ???????, ??????????, ??, ???, ????????? ? ????????????? ?????? ?????? ?????? ???????? ??????. ??????? ????? ???, ??????? ??? ???????? ???? ????? ????????? ?? ???????? ??? ??????? ?????? ???.

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???-????: ??????, ????????, ???? ?????, ????????????, ?????, ???????????, '? ???????'.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Water Quality, Seasonal Variation, Physico-Chemical Parameters, TDS, Hardness, Dissolved Oxygen, Water Quality Index.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The proposed project offers a web-based chess system with dual functionality: Play Mode for normal play and Learn Mode with AI support for move validation, hints, and optimal move suggestions. There is also a Puzzle Mode for tactical training with pre-set scenarios, and a Post-Game Review Module for analysis of accuracy, errors, and decision time. The complexity of the system is in combining deterministic rule validation, adaptive AI search depth based on difficulty levels, natural language processing interfaces for voice-controlled move execution, and statistical models for performance analysis. The system employs chess.js for rule validation, Stockfish.js for move calculation, Web Speech APIs for voice automation, and gamification through achievement patches. The combination of game logic, AI calculation, and speech functionality provides a seamless platform for both play and learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chess Learning System, Interactive Chess Training, Voice-Controlled Chess, Piece Movement Visualization, User Interface Design, Game Automation, Skill-Based Customization, Human-Computer Interaction, Web-Based Chess Application)

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper examines gendered trauma in Bapsi Sidhwa's An American Brat, focusing on Feroza Ginwalla and what she goes through as an expatriate. When Feroza leaves Pakistan for the United States, her inner struggles only get sharper--she faces not just culture shock but even tighter patriarchal pressure. Using trauma theory, especially Cathy Caruth's ideas around belatedness and fractured identity, alongside Homi K. Bhabha's "third space" and hybridity, the study shows how Feroza's trauma isn't just personal--it's shaped by her gender. Her journey through sexual awakening, racial bias, forbidden love, and being pushed away by her family reveals how women's bodies turn into battlegrounds for cultural fears in a global setting. In the end, the paper argues that trauma for expatriates in this novel doesn't come just from being uprooted. It grows out of the tangle of gender, religion, and life in the diaspora.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Gendered trauma, expatriation, hybridity, patriarchy, diaspora, identity crisis, transnationalism.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The present study examined the relationship between academic achievement and family environment among Pre-University College students in Kalaburagi city, Karnataka. The study also compared academic achievement and family environment based on gender, locality, type of institution, and type of college management. A descriptive survey method was adopted. A sample of 800 Pre-University students was selected using random sampling technique. Academic Achievement was measured using students' marks, and Family Environment was measured using a standardized Family Environment Scale. Pearson's Product Moment Correlation (r-test) was used to determine the relationship between academic achievement and family environment among different groups. The results revealed a significant positive relationship between academic achievement and family environment among male, female, urban, and rural students. The findings indicate that a favorable family environment contributes positively to students' academic achievement.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Academic Achievement, Family Environment, Pre-University Students, Gender, Locality, Correlation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Agriculture acts as an important factor in ensuring food supply and pillar for economic development, but current farming method faces many challenges such as unpredictable weather, crop diseases, and insufficient access to equipment, and fluctuating market prices. These issues majorly affect the small and marginal farmers, resulting in reduced crop production and income. To overcome these issues, the system "TechFarm: Your Personalized Farm Assistant" provides a smart and user-friendly web-based digital platform that includes weather forecasting with alert advisory through the use of API's, crop planning and scheduling for crop, disease detection by image processing, equipment sharing services, and real -time market price update. The system uses trustworthy third party API's to provide accurate information.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

TechFarm, Crop Disease Detection, Weather Forecasting, Equipment Sharing, Market Price Analysis, and Crop planning and scheduling.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Mobile applications often request sensitive permissions such as camera, microphone, location, contacts, and storage, which can threaten user privacy and data security. The lack of centralized monitoring mechanisms makes it difficult for users to clearly understand how their personal data is accessed and utilized. This study proposes a Privacy Dashboard for Android Applications that collects and analyzes permission and usage data through Android system APIs. The system evaluates application risk levels using rule-based scoring techniques and generates privacy scores for better transparency. It provides real-time monitoring and interactive graphical visualizations to present privacy insights in a user-friendly manner. Experimental evaluation demonstrates that the system is responsive, accurate, and effective in enhancing user awareness. The framework ultimately supports informed decision-making and strengthens mobile privacy protection.

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Creative Commons Attribution 4.0 and The Open Definition

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Privacy Dashboard, Android Applications, Mobile Privacy, Permission Monitoring, Usage Statistics, Privacy Risk Assessment, Data Security, Android Permissions, Application Analytics, User Privacy Protection

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The global fashion industry is increasingly criticized for high carbon emissions, excessive water consumption, chemical pollution, and dependence on synthetic materials. In contrast, traditional textile techniques rooted in indigenous knowledge systems demonstrate environmentally responsive production models grounded in ecological balance and localized economies. This study critically evaluates selected Indian textile practices including natural dyeing, handloom weaving, and eco-friendly fibre processing as sustainable production systems. Drawing on peer-reviewed literature, government reports, and sustainability assessments, the paper analyzes environmental performance indicators such as carbon intensity, water usage, chemical load, and energy dependency alongside socio-economic factors including employment generation and decentralization of production. Comparative evaluation highlights reduced fossil fuel dependence in handloom weaving, biodegradability of natural fibres, and lower toxicity profiles in plant-based dyeing systems. The study further examines structural constraints including income instability, scalability challenges, and market integration barriers. By developing a conceptual sustainability framework, the paper argues that indigenous textile systems represent empirically grounded, low-carbon production models aligned with contemporary sustainable development objectives. Strategic policy support and hybrid innovation approaches are necessary to enhance their long-term viability within modern fashion economies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Indigenous Textiles; Sustainable Fashion; Handloom Weaving; Natural Dyeing; Craft Economy; Sustainable Production

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

It is becoming more widely acknowledged that chronic diabetes mellitus (DM) increases the incidence of neurodegenerative illnesses, including Parkinson's disease (PD). Oxidative stress as well as neuroinflammation stand highlighted as important, interconnected drivers for dopaminergic neurodegeneration among the major mechanisms connecting these two disorders. Diabetes-related chronic hyper glycemia results in a compromised antioxidant defense system, increased generation in reactive oxygen molecules (ROS) and compromised mitochondrial activity. Due to their great susceptibility to oxidative insults, dopamine-producing neurons of the substantia nigra are especially affected by the prolonged oxidative stress caused by these alterations. Furthermore, neuroprotective pathways may be disrupted by poor insulin transmission in the brain, making neurons even more susceptible to oxidative & inflammatory assaults. Oxidative stress & neuroinflammation are key and perhaps changeable pathways in diabetes-induced neurodegeneration, even though other elements like mitochondrial malfunction and protein aggregation (like ?-synuclein) also contribute to Parkinson's disease pathogenesis. ?-synuclein aggregation & dopaminergic cell death are two classic PD diseases that are caused by the synergistic combination of oxidative stress and neuroinflammation, which upsets neuronal homeostasis. These results highlight how crucial it is to target oxidative & inflammatory pathways in diabetic populations help prevent or delay the emergence of Parkinson's disease. One promising approach to risk reduction and therapeutic intervention is to address these pathways.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diabetes, Oxidative stress Neuroinflammation, Parkinson

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Artificial Intelligence (AI) is influencing personal lifestyles and professional environments across the globe, with tech-forward cities like Hyderabad at the forefront. This study presents findings from a qualitative statistical survey that explores AI's impact on daily routines and workplace practices in Hyderabad. Drawing on responses from 250 participants from various sectors, the study reveals the dual nature of AI's role: enhancing convenience and productivity on one side while raising concerns around job security and privacy on the other the paper concludes with insights into how individuals and organizations can adapt to AI's continuing evolution.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Daily Life, Workplace Automation, Hyderabad, Human-AI Interaction, Job Displacement, AI Ethics, Technology Adoption, Smart Devices, AI Integration.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Diabetes mellitus is a complex metabolic disease characterized by persistent hyperglycemia arising from defects in insulin secretion, insulin responsiveness, or both. Despite the availability of numerous therapeutic options, diabetes continues to impose a substantial clinical and socioeconomic burden due to its progressive nature and associated complications. Therapeutic paradigms have evolved significantly, shifting from conventional glucose-lowering approaches to multidimensional strategies that address cardiovascular, renal, and metabolic risks. This review critically evaluates established and emerging treatments for diabetes mellitus, including lifestyle-based interventions, traditional and novel pharmacological agents, advanced insulin formulations, and innovative therapeutic platforms. Particular emphasis is placed on mechanistic diversity, clinical outcomes, safety considerations, and future directions aimed at achieving durable glycemic control and ?-cell preservation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diabetes mellitus, antidiabetic therapy, insulin analogues, incretin system, SGLT-2 inhibitors, emerging treatments.

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Creative Commons Attribution 4.0 and The Open Definition