Volume 14 | Issue 4 |

 Abstract

Social media platforms such as Instagram have experienced rapid growth over the past decade. However, this expansion has also introduced significant risks, including fake profiles, impersonation attacks, spam conversations, and phishing attempts. Malicious actors frequently exploit deceptive profile information and social engineering methods, making it genuinely difficult for ordinary users to spot fraudulent accounts. Existing detection solutions are mostly controlled by the platforms them- selves and operate as closed, opaque systems that offer very little transparency or direct control to individual users.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fake account detection, Instagram authenticity, machine learning, TF-IDF, Random Forest, XGBoost, Naive Bayes, heuristic analysis, social media security, risk scoring.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The ancient Uttarapatha, meaning the "Northern Road," represents one of the earliest extensive trade networks in the Indian subcontinent, serving as a vital artery for interaction between South Asia, Central Asia, and the wider Eurasian region. Predating the widespread recognition of the Silk Route, this corridor facilitated connections among prominent urban centres, including Taxila, Mathura, Varanasi, and Pataliputra. Through these linkages, it enabled not only commercial exchange but also the movement of ideas, cultures, and religious traditions.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Uttarapatha, Silk Route, Ancient Indian Trade Routes, Trans-Asian Trade Networks, Cultural Exchange, Central Asia, Connectivity, Economic History.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In Jain meditative wisdom, a mantra is defined as a word or phrase in which the power of pure souls is inherent. Central to this tradition is the sacred mantra Om Arham Namaha. As stated in the Arham A??a?ga Yog ?atakam (v. 25), "????? ???????? ??????? ??????????????????" ? "Arham is the seed-letter principle, the single supreme essence of all mantras." This study explores the linguistic, symbolic, and transformative dimensions of this foundational sound

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 Keywords

Om Arham Namaha, B?ja-ak?ara, Arham Dhyan Yog, Jainism & Meditation, Muni Pra?amya Sagar, Contemporary Yoga Studies

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Formula 1 (F1) motorsport operates at the intersec- tion of high-speed engineering and data-driven decision making, where fractions of a second determine competitive outcomes. Despite the existence of publicly accessible telemetry libraries such as FastF1 and structured APIs like the Ergast Developer API, the raw data they expose remains largely inaccessible to students, independent analysts, and motorsport enthusiasts due to the technical complexity involved in extraction and interpretation. This paper presents the design and development of an interactive web-based platform that consolidates F1 telemetry and race data into a structured analytical dashboard. The system integrates data pipelines built on FastF1 and Ergast, performs preprocessing to normalize lap times, telemetry channels, and sector timings, and exposes processed results through a responsive frontend built with ReactJS. Core analytical features include lap-time differential computation, multi-driver telemetry overlays, speed- versus-distance profiles, sector performance comparisons, and consistency metrics derived from statistical measures of lap- time variance. The architecture follows a modular layered design encompassing an API controller, data processor, database storage layer, and visualization module. Evaluation confirms that the platform accurately renders historical race sessions and provides meaningful performance insights in an intuitive visual format. The work demonstrates practical application of data engineering, dynamic visualization, and web application development within the domain of real-world motorsport analytics.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Formula 1, FastF1, Telemetry Analysis, Race Data Visualization, Lap Time Comparison, Driver Performance, Ergast API, Web Dashboard, Data Preprocessing, Interactive Charts

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Understanding customer behavior in online shop- ping environments plays a central role in shaping marketing strategies and building personalized user experiences. This paper presents a machine-learning-based framework that leverages clickstream behavioral data to perform customer segmentation and deliver targeted product recommendations. The study utilizes a publicly available e-commerce dataset from Kaggle, which contains detailed records of user interactions such as product browsing, add-to-cart actions, and purchase completions. From this dataset, a set of behavioral features is derived that collec- tively captures spending patterns, order frequency, engagement intensity, and sensitivity to discounted products. These features serve as inputs to the K-Means clustering algorithm, an unsuper- vised machine learning technique that partitions customers into groups sharing similar behavioral characteristics. To improve the interpretability of the resulting clusters, Principal Component Analysis (PCA) is applied to reduce the multi-dimensional feature space into three principal components representing spending and order intensity, engagement behavior, and discount sensitivity. The reduced representation enables effective visualization of customer clusters and supports analysis of inter-group behavioral differences. Leveraging the identified customer segments, the system generates segment-specific product recommendations and delivers them through an automated email notification pipeline. The proposed approach demonstrates how clickstream-based behavioral analytics, combined with unsupervised learning and dimensionality reduction, can support meaningful personalization and targeted marketing in e-commerce environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Clickstream Data, Customer Segmentation, K-Means Clustering, Principal Component Analysis, Personalized Recom- mendations, E-Commerce, Behavioral Analytics, Unsupervised Machine Learning

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Inguinal hernia is one of the most common surgical conditions seen in adult males, especially among those involved in strenuous physical work. Direct inguinal hernia occurs due to weakness of the posterior wall of the inguinal canal and may extend into the scrotum in long-standing cases. The coexistence of inguinal hernia in a patient with a past history of abdominal tuberculosis is uncommon and may create diagnostic and management challenges. We present the case of a 39-year-old male who complained of right inguinoscrotal swelling for 5-6 months associated with mild pain. The swelling was reducible and had a positive cough impulse. Ultrasonography confirmed a right direct inguinoscrotal hernia with a 1.2 cm defect and protrusion of bowel loops on Valsalva maneuver. The patient had a past history of abdominal Koch's, ascites, and diagnostic laparoscopy, for which anti-tubercular treatment had been completed. Routine laboratory investigations were within acceptable limits for surgery. The patient underwent right open hernioplasty with polypropylene mesh under spinal anesthesia. The intraoperative and postoperative period was uneventful. The patient recovered well and was discharged in stable condition. This case highlights successful management of direct inguinoscrotal hernia with mesh hernioplasty in a patient with previous abdominal tuberculosis and supports the effectiveness of conventional surgical treatment in such presentations.

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 Keywords

Keywords: Inguinal hernia, Direct inguinal hernia, Inguinoscrotal hernia, Hernioplasty, Mesh repair, Abdominal tuberculosis

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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

 Keywords

College Event Management, Event Registration, Razorpay Integration, Payment Verification, QR-Code Entry Pass, Attendance Tracking, Analytics Dashboard, CSV Reporting, React, Spring Boot, MySQL, JWT, ZXing QR, html5-qrcode, Chart.js

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's digital era, online recruitment platforms have made job searching easier, but they also present challenges such as irrelevant job recommendations and the increasing presence of fraudulent job postings. To address these issues, this project proposes a Resume-Centric Job Recommendation and Fake Job Detection System using machine learning techniques. The system analyzes uploaded resumes by extracting text from PDF files and identifying key skills and competencies through keyword processing. It then matches these skills with job descriptions obtained from real-time job search APIs. To measure the relevance between a candidate's profile and job descriptions, TF-IDF (Term Frequency-Inverse Document Frequency) is used for feature extraction, and cosine similarity is applied to compute a similarity score, enabling accurate and personalized job recommendations. Additionally, the system enhances user safety by detecting fraudulent job postings using a Logistic Regression classifier trained on labeled job data to identify suspicious patterns and classify listings as genuine or fake. The complete system is implemented using the Flask framework, providing an interactive and user-friendly web interface where users can upload resumes and filter job results based on criteria such as location and role. Experimental results demonstrate that the proposed system improves recommendation accuracy while significantly increasing trust and reliability in online recruitment platforms by effectively identifying fake job listings.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Resume-Centric Job Recommendation, Fake Job Detection, Logistic Regression, Machine Learning, TF-IDF Vectorization, Cosine Similarity, Skill Matching, Recruitment Fraud Analysis,Flask-Based Web System.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study examines how employer branding influences both the attraction of potential candidates and the retention of existing employees. As competition for skill talent intensifies, organizations increasingly rely on strong and authentic employer branding to differentiate themselves in the job market. The research explores key factors which shapes employee perceptions and hiring decisions. Using a descriptive research design and primary data collected from about 50 respondents, the study analyzes how employer branding affects job seekers application intentions and employees' willingness to remain with their current organizations. The findings reveal that a positive employer brand significantly enhances talent attraction, strengthens engagement, and reduces turnover, while inconsistencies between the brand message and actual employee experience negatively impact trust and retention. The study concludes that organizations must invest in transparent communication, employee well-being, career development, and strong leadership to build a credible employer brand that supports long-term workforce stability. Future research may explore industry-wise comparisons and the evolving impact of remote and hybrid work on employer branding strategies.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Keywords- Employee Retention, Employee Experience, Employer Branding, Talent Attraction, Turnover Reduction.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

ABSTRACT Knee joint pain is a common musculoskeletal problem among the geriatric population, significantly affecting their mobility and quality of life. This study aimed to assess the effectiveness of hot water application with Epsom salt versus hot water application alone on the level of knee joint pain among geriatrics in a selected area at Karungal, Kanyakumri District. A true experimental research design with a quantitative evaluative approach was adopted. The study included three groups: control group, experimental group I (hot water application with Epsom salt), and experimental group II (hot water application alone). The independent variables were hot water application with Epsom salt and hot water application, while the dependent variable was the level of knee joint pain. Data were collected using a structured interview schedule, including demographic variables and a numerical pain rating scale. The tool's reliability was confirmed using the test-retest method (r = 0.9). A pilot study established feasibility. The conceptual framework was based on the Gate Control Theory by Melzack and Wall. The findings revealed a significant reduction in knee joint pain levels in both experimental groups compared to the control group. However, experimental group I showed greater effectiveness than experimental group II. Statistical analysis (unpaired 't' test) indicated a significant difference between the two interventions. There was no significant association between post-test pain levels and selected demographic variables. The study concluded that hot water application with Epsom salt is more effective than hot water application alone in reducing knee joint pain among geriatrics. The intervention is simple, cost-effective, and can be recommended as a non-pharmacological method for pain management in elderly individuals.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Knee joint pain, Geriatrics, Hot water application, Epsom salt, Non-pharmacological intervention, Pain management, Musculoskeletal disorders, Numerical pain rating scale, Gate Control Theory, Experimental study, Elderly care, Hydrotherapy

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Creative Commons Attribution 4.0 and The Open Definition