Volume 13 | Issue 10 |

 Abstract

Abstract--In today's competitive job market, it is essential for candidates to have well-structured and Application Tracking System (ATS)-friendly resumes that align with job requirements. This project presents an AI-based Resume Analyzer and Job Matching System developed using Machine Learning and Natural Language Processing (NLP) techniques. The system analyzes a user's resume to identify grammatical errors, formatting issues, and ATS compatibility. It also evaluates the similarity between a candidate's resume and a given job description by applying text embedding and similarity scoring models. Using algorithms such as TF-IDF and cosine similarity, or transformer-based embeddings like BERT, the system calculates a match percentage to determine how closely the resume fits the job criteria. If the similarity score is low, the model provides suggestions for improvement, including missing keywords or recommended sections to make the resume more ATS-friendly. The entire process is implemented locally using Python, ensuring data privacy, offline accessibility, and fast execution. This intelligent system aims to assist students, job seekers, and recruiters by automating the resume evaluation process, improving candidate profiles, and enhancing the chances of shortlisting in real-world recruitment systems.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

AI Resume Analyzer, Machine Learning, Natural Language Processing, ATS Compatibility, Job Description Matching, Text Mining, Semantic Similarity, Python, NLP Pipeline, Career Recommendation System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Water quality is a vital factor influencing human health, industrial productivity, and agricultural yield. Hard water, containing high concentrations of dissolved minerals such as calcium and magnesium, causes scaling in pipelines, reduces the efficiency and lifespan of household appliances, and increases soap consumption. Traditional water softening systems often lack continuous monitoring and automated control, leading to inefficient operation, excessive resource consumption, and unpredictable water quality. This project proposes the design and development of a Hard Water Softener with Automated Quality Monitoring, capable of real-time measurement of pH, Total Dissolved Solids (TDS), and specific mineral concentrations. The system integrates an ion-exchange resin softening unit with an array of digital water quality sensors. These sensors feed continuous data to a microcontroller-based control unit, which analyzes the parameters and automatically activates or regulates the softening process as per predefined thresholds. The monitoring system is complemented by an LCD display and IoT- enabled remote access, allowing users to track water quality trends and system performance from anywhere. Index Terms--Hard Water, Water Softener, Automated Quality Monitoring, pH Sensor, Total Dissolved Solids (TDS), Mineral Detection, Ion Exchange, Internet of Things (IoT), Smart Water Management, Real-Time Monitoring, Predictive Maintenance, AI Integration, Secure IoT Systems, Water Treatment Automation.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hard Water, Water Softener, Automated, Quality Monitoring, pH Sensor, Total Dissolved Solids (TDS), Mineral Detection, Ion Exchange, Internet of Things (IoT), Smart Water Management, Real-Time Monitoring, Predictive Maintenance, AI Integration, Secure IoT Systems, Water Treatment Automation

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid proliferation of Internet of Things (IoT) devices in modern power systems has transformed the landscape of energy management, enabling real-time monitoring, predictive maintenance, and decentralized control. However, the exponential growth in data generation poses significant challenges for conventional cloud computing (CC) infrastructures, including high latency, bandwidth congestion, and security vulnerabilities. To address these limitations, emerging paradigms such as fog computing (FC) and edge computing (EC) offer localized processing closer to the data source, reducing latency and optimizing network resources. This review paper examines the integration of CC, FC, and EC within smart grid architectures, highlighting their technical advantages, implementation challenges, and contributions to enhancing system efficiency, resilience, and adaptability. Furthermore, the paper analyzes hierarchical EC architectures, including device, edge server, and cloud layers, and their role in enabling real-time energy management, fault detection, and adaptive control. The findings underscore the critical role of hybrid computing models in supporting large-scale, latency-sensitive, and data-intensive smart energy systems, while emphasizing the need for continued research in secure, scalable, and intelligent computational

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Smart Grids, Edge Computing, Cloud-Fog Integration

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

India's tribal communities possess a wealth of traditional medicinal knowledge, intricately linked to their cultural practices and local biodiversity. This ethnomedicinal heritage not only offers alternative healthcare solutions but also plays a pivotal role in conserving medicinal plant species and promoting sustainable healthcare practices. However, rapid modernization, deforestation, and the erosion of traditional lifestyles threaten the preservation of this invaluable knowledge. This qualitative secondary research delves into the significance of tribal medicinal knowledge in biodiversity conservation and sustainable healthcare. By analysing ethnobotanical surveys, government reports, and academic studies, the research highlights how indigenous practices contribute to the sustainable use of medicinal plants and the challenges faced in preserving this knowledge. The study underscores the need for collaborative frameworks that respect and integrate tribal knowledge into broader conservation and healthcare strategies. It advocates for policies that recognize the contributions of tribal communities, support the documentation of traditional practices, and ensure the sustainable harvesting of medicinal plants. By valuing and preserving tribal medicinal knowledge, we can foster biodiversity conservation and promote sustainable healthcare solutions that are culturally relevant and ecologically sound.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Tribal Medicinal Knowledge, Biodiversity Conservation, Sustainable Healthcare, Ethnomedicine, Indigenous Practices

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

"A Pre-Experimental Study To Assess The Effectiveness OF Education Package On Knowledge Regarding ABG Analysis Interpretation Among Critical Care Nurses Of Selected Hospitals Of Punjab" Harpreet Kaur Research Scholar, Faculty of Nursing, DBU, Mandi Gobindgarh, Punjab Sukhmanpreet Kaur Associate Professor, Faculty of Nursing, DBU, Mandi Gobindgarh, Punjab. Background-The ABG test is a critical diagnostic tool used to assess a patient's acid-base balance, oxygenation, and ventilation status. It measures acidity or alkalinity of blood, Partial pressure of carbon dioxide (respiratory component) Bicarbonate level (metabolic component) This test is commonly used in critical care, respiratory therapy, and emergency settings to evaluate conditions like respiratory failure, metabolic disorders, and shock. Nurses play a vital role in the clinical application of ABG results. They recognize abnormal values and correlate with patient symptoms. Objective -The aim of the study was to improve knowledge regarding ABG analysis interpretation among critical care nurses of selected hospitals of Punjab. Material and Method-A Quantitative approach with pre- experimental research design was used for the study. Total 100 Critical care nurses were working different critical care units were enrolled of selected hospitals of Punjab.Non randomized convenient sampling technique was used. A pre-validated, self-structured questionnaire was developed to assess the effectiveness of education package of knowledge regarding regarding ABG analysis interpretation among critical care nurses of selected hospitals of Punjab. Package On Knowledge Regarding ABG Analysis Interpretation was developed and implemented. It is divided in three parts.Part1 deals with knowledge related to ABG test, Part II deals with knowledge related to ABG procedure and Part III deals with knowledge related to ABG Interpretation. Post-Test was conducted after one week of nurse led education package of knowledge regarding regarding ABG analysis. Results- The majority of the Critical Care Nurses are between 20-30 years i.e. 70%, the next main group is 31-40 i.e. 29%. Most of the critical were nurses are female (94%). (63% of the working were GNM, 24% were B.Sc. and 11% were P.B.BSc and 2% were M.Sc. Nursing A significant majority have 0-5 year experience 84%.The pre -test knowledge score was the majority of participants (88%) score in the "Poor" category range i.e. (0-49), with 10% scoring in the "Average" range i.e. (50-79) and only 2% achieving a "Good" range score i.e. (80-100) This indicates that critical care nurses have lower knowledge of ABG analysis interpretation before the interventions There was a significant improvement in knowledge scores from pre -test (Mean = 13.60) to post test (Mean = 33.59), with a T-value of 42.319 and a P-value <0.001, indicating the intervention had a strong positive effect In the post test. Conclusion-, In the present study Education Package regarding the Interpretation of ABG analysis among critical care unit nurses was effective, as it improved the knowledge related to ABG test procedure and interpretation of critical care nurses.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Words -Critical care nurses, ABG Analysis interpretation, Education Package

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

often rely on cloud based APIs. This increases the concern about data privacy, cost and dependence on third party vendors. This paper presents "THE BRAIN AI", a flexible and private framework to build a solution of concert of people as multi-documents analysis with interaction with document with chat interface. This system use locally hosted LLMs using Ollama framework, which keep all data locally, It also include a dual model knowledge extraction pipeline that support faster NLP analyse the document uploaded, and user can upload document in various format and capable to process all data parallel and storing structured data knowledge in the entire knowledge based. This system offers a secure, adaptable and powerful tool for managing data both at the personal and enterprise level. THE BRAIN AI provides a practical way to take advantage of local language models for document analyses and making it ideal for users who need data protection, and use interfaces without even connecting with the internet.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Retrieval Augmented Generation(RAG),Large Language Model(LLM), Ollama, Natural Language Model, Parallel Processing, Data privacy, Document Processing.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The study examines the effects of stigma on rape survivor reintegration in India, with attention to emotional wellbeing, mental health, and access to justice and jobs. The aims were to assess the psychological and social effects of stigma and to identify barriers to survivor reintegration. Through a descriptive and exploratory study design, 200 respondents were surveyed using a stratified random sample via structured questionnaires, and the data were analyzed using correlation and regression techniques. The results indicated that perceived stigma had a statistically significant effect on survivors' mental health, which increased distress, self-blame, and decreased quality of life. Furthermore, stigma was a strong predictor of barriers to accessing justice and jobs, which hampers long-term reintegration. The study concludes that responses to stigma must include survivor-centred interventions, community sensitization, and policy-level change to promote dignity, empowerment, and sustainable reintegration for survivors.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Societal stigma, rape survivors, reintegration, mental health, justice barriers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Microfinance has emerged as a vital tool for promoting financial inclusion and fostering women's empowerment, particularly in rural India. This study presents a five-year analysis (2021-2025) of microfinance initiatives, focusing on their impact on women's economic, social, and psychological empowerment through Self-Help Groups (SHGs) and women-led micro-enterprises. Using data from NABARD, DAY-NRLM, and government reports, the study tracks growth in women beneficiaries, SHG membership, and entrepreneurial ventures over the period. The findings indicate consistent economic empowerment, with increased income, savings, and asset ownership among women participants. Social and psychological empowerment has also improved, reflected in greater decision-making authority, mobility, self-confidence, and leadership roles. However, challenges such as over-indebtedness, limited market access, dependency on external agencies, and financial literacy gaps persist. The study highlights the critical role of Government schemes, Digital financial inclusion, and capacity-building programs in enhancing the sustainability and scalability of microfinance initiatives. Overall, the five-year analysis demonstrates that microfinance serves as a multi-dimensional enabler of women's empowerment, with long-term benefits dependent on supportive policies, training, and market linkages.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Micro Finance, SHGs , Micro-enterprises Empowerment, NABARD and Supportive policies

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Achieving work-life balance has become a crucial difficulty in the rapidly changing information technology (IT) sector, especially for female professionals who frequently juggle a number of personal and professional obligations. With an emphasis on how more control over work tasks, scheduling, and decision-making leads to better balance between the domains of professional and personal life, this study investigates the impact of job autonomy on the work-life balance of female IT employees. The study uses quantitative techniques to examine the connection between job autonomy and perceived work-life balance using a standardized questionnaire given to female IT professionals. The results show a strong positive correlation, suggesting that greater workplace autonomy improves workers' capacity to successfully balance work responsibilities with their personal lives.In order to improve work-life balance for women in the IT industry, the study emphasizes the significance of encouraging flexible and independent work conditions. These observations have important ramifications for organizational procedures and HR policies meant to promote gender-sensitive, employee-focused workplaces.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Job autonomy ,Work-life balance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Experiential learning, emphasizing active engagement and reflection, is pivotal in teacher education. This study evaluates one week experiential learning workshop's impact on the knowledge, attitudes, and pedagogical readiness of 45 student teachers from St. Ann's College of Education, Secunderabad. Employing a quasi-experimental one-group pre-test/post-test design complemented by a perception survey, results show statistically significant improvement in cognitive understanding (t = 11.71, p < 0.05) and positive shifts in perceptions toward learner-centered pedagogy. Qualitative data indicate enhanced confidence in crafting experiential activities, promoting equitable participation, and adopting reflective assessment strategies. The findings reinforce experiential learning as an effective, scalable professional development model that nurtures reflective, inclusive, and active teaching practices.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Experiential Learning, Teacher Education, Professional Development, Reflective Practice, Pedagogy

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Creative Commons Attribution 4.0 and The Open Definition