Volume 14 | Issue 4 |

 Abstract

The exponential accumulation of digital documentation across professional domains has rendered manual information retrieval both impractical and error to prone. Cloud-based question-answering (QA) solutions, while capable, raise significant concerns regarding data confidentiality, unpredictable hallucinated outputs, and reliance on continuous internet access. This paper introduces InsightDoc, a locally executed, privacy-centric document QA framework that couples Term Frequency-Inverse Document Frequency (TF-IDF) retrieval with a locally hosted, lightweight large language model (LLM) to generate answers strictly from user-supplied PDF documents. The proposed architecture operates entirely offline by deploying the Qwen 1.8B language model through the Ollama runtime environment. The system extracts and normalizes textual content from PDFs, partitions it into sentence-bounded chunks, constructs a TF-IDF sparse index, retrieves the most contextually relevant passages via cosine similarity, and delivers the assembled evidence to the LLM for grounded answer generation. Evaluation on a 50-question benchmark yields a retrieval Precision@5 of 0.76, an F1 Score of 0.73, and a mean retrieval latency well below 0.2 seconds, with zero observed hallucinations. InsightDoc provides a practical and resource-efficient baseline for offline document QA, ensuring verifiable data sovereignty.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Retrieval-Augmented Generation (RAG), TF-IDF Vectorization, Local Large Language Model, Document Question Answering, Cosine Similarity, Information Retrieval, Ollama, Privacy-Preserving AI.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sushruta is venerated as the primordial surgeon who pioneered reconstructive and aesthetic procedures, earning the epithet "Father of Plastic Surgery." His magnum opus, the Sushruta Samhita, remains the most comprehensive surgical compendium in Ayurveda, meticulously delineating practical operative techniques. Conceived as a didactic manual, it was intended to guide physicians in delivering holistic patient care. Equally eminent, Acharya Charaka endorsed Shalya Tantra--the surgical discipline--for conditions necessitating urgent intervention, such as Bhagandara (fistula), Arsha (hemorrhoids), and Mudhgarbha (obstructed labor). The surgical armamentarium described in Ayurvedic treatises was ingeniously fashioned from organic materials including timber, lithic implements, broad foliage, and arboreal branches. A distinctive convention was the christening of instruments after fauna and avian species, a nomenclatural practice that persists in modern surgical taxonomy. Rigorous Yogya (preparatory training) was mandated for apprentices prior to undertaking actual operations. The Sushruta Samhita furnishes exhaustive expositions on surgical classifications, instrumentation, suturing methodologies, ligatures (Bandhana), protocols of informed consent, and the establishment of operative theatres (Shalyagar). Remarkably, these principles continue to resonate as foundational standards in contemporary surgical practice.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Mudhagarbha, Shalyagar, Bandhana

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Rabindra Nath Tagore, the embodiment of wisdom and perfection occupies the most coveted and aspired throne in the realm of Indian English literature. This most versatile grate of his time, Rabindra Nath Tagore left no genre of literature un-attempted. Poems, Novels, Plays, short stories, various kinds of prose and miscellaneous writing followed ceaselessly from his fertile heart and mind. Although he left no genera of literature untouched, he is mostly acclaimed for his achievement as a poet, specially for his Magnum Opus 'Gitanjali' for which he won the Nobel Prize in the year 1913. His poetic talent and exposure reached new heights as he was acclaimed all over the World with the publication of Gitanjali in 1912 . This paper is an attempt to explore the underlying spiritualism in the poetry of Rabindra Nath Tagore, specially in Gitanjali and the way Tagore achieves spiritual enlightenment in his poetry by dwelling in the World of the Divine.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Spiritualism, Eco-Feminism, Ecology, Deep Ecology, divine, Union

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Sportswear clothes are designed with consideration of performance, comfort, and functionality for those people taking part in physical exercise with design factors changing with varying levels of exercise intensity. The most frequent types of fabrics used include polyester-cotton blend which comes in two major designs; compression and loose designs. This work will focus on defining the characteristics of each material and fit in terms of comfort and physiological performance. Every material and fit have advantages and disadvantages. Polyester-cotton blends are soft and comfortable although they retain moisture after prolonged exercise periods. Polyester allows for better moisture removal and faster drying as well as being durable. Compression design ensures proper muscle support and reduces exhaustion although when tight it can create discomfort for the user. Loose design improves airflow and flexibility but provides little stability during rigorous exercises. Finally, materials and designs should be chosen depending on personal comfort perception, exercise level, and period. However, the use of polyester sportswear is considered the best because of its moisture management and performance.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Sportswear, Polyester, Cotton, Compression, Breathability, Comfort, Performance

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Rotato cuff injury, Ultrasound therapy, Kinesio taping, Shoulder pain, Physiotherapy, Sports injuries

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid expansion of the electric vehicle market has increased the need for transparent and accurate cost estimation methods for consumers, manufacturers, and policymakers. This paper presents a machine learning-based framework for the analysis and prediction of electric vehicle costs using technical and market-related vehicle attributes. A structured dataset containing features such as brand, acceleration, top speed, battery range, energy efficiency, fast-charging capability, plug type, body style, market segment, and seating capacity was used for model development. Data preprocessing techniques including missing value handling, feature encoding, normalization, and train-test splitting were applied to improve prediction quality. Multiple supervised learning algorithms, namely Linear Regression, Decision Tree, Random Forest, Support Vector Machine, and Artificial Neural Network, were trained and compared using standard regression metrics such as RMSE and R-squared. Experimental results showed that Random Forest and ANN models achieved superior predictive performance compared to traditional approaches, with Random Forest offering an effective balance between accuracy and computational efficiency. A web-based user interface was also developed to allow users to enter vehicle specifications and obtain real-time estimated costs. The proposed system demonstrates that machine learning can provide reliable and practical support for EV price estimation, helping reduce uncertainty in purchasing decisions and market analysis.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Electric Vehicles, Machine Learning, Cost Prediction, Random Forest, Artificial Neural Network, Price Estimation, Regression Analysis, EV Market

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study explores the evolving financial independence of women and its influence on their consumer behavior. Traditionally dependent on male family members for financial support, modern women are increasingly self-reliant, leading to a significant shift in their consumption patterns. This shift reflects greater autonomy in purchasing decisions and the freedom to acquire desired goods without restriction. The paper analyses female consumer behavior, examining how income levels and personal preferences influence buying patterns. Based on responses from female participants, the study aims to examine and interpret behavioural trends, drawing relevant conclusions about the impact of financial independence on consumption choices. The study focuses on female respondents to analyse behavioural changes in consumption and spending habits. Also, it investigates how increased autonomy influences women's purchasing decisions, particularly their freedom to buy desired products. The behavioral patterns are observed through primary data collection from female consumers, enabling informed conclusions. The significance of the study is to offer insight into the evolving role of women in the economy and the implications for marketers and consumer researchers.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Female, consumer behavior, buying, consumption, Independence

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The overconsumption of medicine has become a pressing concern in public health, particularly in regions where healthcare systems are overburdened or inadequately regulated. This research paper investigates the growing trend of medication overuse, characterized by self-medication, irrational prescriptions and the misuse of both over the counter and prescription drugs. Key drivers include increased accessibility to pharmaceuticals, lack of awareness among the public, insufficient regulatory enforcement, and the influence of aggressive pharmaceutical marketing. Commonly overused drugs - such as antibiotics, sedatives and antacids are often consumed without proper medical supervision, leading to serious health consequences like drug dependency, organ toxicity, weakened immunity and increased drug reactions. Findings suggest that among 125 respondents through online survey , the majority of people (49.2%) consume cold/flu medicines which indicates a tendency toward self-treatment for common ailments which might lead to dependency or addiction if not properly guided while 91.9% people want to know more about safe medicine use , during menstruation 77.5% women do not take medication while 22.5% does which must be monitored to avoid addiction and long term side effects , 35.6% women rely more on herbal remedies than modern medications , almost 80% parents do not give medications to their child without prescription while 16.7% parents does which indicate a serious need for parental guidance , child safe drug practices. This research concludes by recommending rational use of drugs, public health awareness and foster more responsible medication practices.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Overconsumption, Self-medication, Drug misuse, Public Health, Antibiotic resistance, Rational drug use.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Acne is one of the most common skin diseases affecting people across different age groups, and accurate classification of lesion types is essential for effective dermatological diagnosis and treatment planning. However, manually assessing acne lesions can be both subjective and time-consuming, which has driven the development of automated computer-aided diagnostic systems. In this context, the authors propose a multiclass deep learning-based object recognition model for acne lesion classification using facial skin images. The system is designed to detect and classify various types of acne lesions, including blackheads, nodules, papules, pustules, whiteheads, as well as background regions. Initially, the skin images undergo preprocessing to enhance quality and reduce noise that could otherwise affect feature extraction. Subsequently, a deep learning model is employed to automatically learn discriminative visual features of different lesion categories. These learned features enable precise multiclass classification of acne lesions present in facial skin images.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Acne classification, skin lesion detection, deep learning, multiclass analysis of skin diseases, and computer-aided dermatology.

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Creative Commons Attribution 4.0 and The Open Definition

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This study examines parental awareness of school-related stress in children among corporate-sector parents in Bengaluru. Using a descriptive quantitative design and a Likert-scale questionnaire, awareness was assessed across behavioral, emotional, communication, and physical domains. Findings indicate higher recognition of observable behavioral indicators, such as irritability and school avoidance, but lower awareness of internal emotional indicators like anxiety and withdrawal. The study highlights the need to improve parental emotional sensitivity, strengthen communication, and implement awareness programs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

parental awareness, school-related stress, children, behavioural indicators, emotional awareness, communication

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Creative Commons Attribution 4.0 and The Open Definition