Volume 13 | Issue 5 |

 Abstract

This study explores the application of machine learning techniques in compensation analytics at Cholamandalam Investment and Finance Company Limited (CIFCL). As organizations increasingly shift toward data-driven decision-making, this research investigates how predictive models can enhance fairness, transparency, and efficiency in compensation management. Using a dataset of employee compensation records, the study applies regression algorithms, feature selection methods, and dimensionality reduction techniques such as PCA to identify key factors influencing salary structures. Polynomial Regression emerged as the most accurate model for predicting compensation, while analysis also revealed strong correlations among salary components and the potential for multicollinearity. The findings underscore the value of machine learning in optimizing pay structures, detecting anomalies, and supporting strategic HR decisions. Despite some limitations related to data size and model complexity, the study demonstrates that AI-driven compensation analytics can significantly improve employee retention, equity, and organizational performance.

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 Keywords

Compensation Analytics, Principal Component Analysis (PCA), Multicollinearity

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Choosing the right career is a pivotal milestone in a student's life and often shapes their future professional trajectory. Traditional career counselling, though valuable, can be influenced by subjective opinions and limited by human bias, accessibility, or lack of data-driven insights. To address this challenge, this paper introduces an Automated Career Counselling System that leverages machine learning to provide personalized career recommendations. By analyzing a student's academic background, practical experience, and soft skills, the system predicts optimal career paths using a trained Random Forest Classifier. Key inputs include GPA, internships, completed projects, communication skills, and other personal competencies. The model was built using Python, with the scikit-learn library for machine learning and Flask for developing a lightweight and responsive web application. The user interface is designed to be intuitive and accessible, allowing students to interact easily with the system and receive actionable insights. The training data consists of a labelled dataset that maps various student profiles to corresponding suitable careers. After training and evaluation, the model demonstrated promising accuracy, confirming its reliability in assisting career decisions. Unlike conventional guidance methods, this system offers a consistent and objective evaluation of students' potential career options. By removing human subjectivity, it ensures that each recommendation is solely based on data and measurable factors, making it suitable for large-scale deployment across educational institutions. Counsellors and administrators can use this system to support a growing student base with consistent quality and efficiency. Looking ahead, the system has strong potential for further enhancement. Integrating real-time labour market data and trends could allow the platform to recommend careers based not only on student profiles but also on current industry demands. Additionally, incorporating automated resume analysis and natural language processing for evaluating written inputs or essays could significantly improve the personalization of suggestions.

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 Keywords

GPA, Support Vector Machines (SVM), decision tree classifiers, communication skills, personal competencies.

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An important turning point in India's educational reform strategy is the National Education Policy (NEP) 2020, which calls for a change from inflexible, segmented academic frameworks to a flexible, multidisciplinary framework. In light of NEP 2020, this topic article critically analyses the theoretical and practical foundations of a multidisciplinary approach, placing it within both indigenous epistemologies and global educational trends. Through the integration of many knowledge streams--such as science, the humanities, the arts, and vocational disciplines--across school and higher education levels, the strategy aims to create an educational system that fosters creativity, critical thinking, and holistic growth. The study examines several important thematic strands, including (i) the philosophical underpinnings of multidisciplinary learning in liberal education models and ancient Indian knowledge systems, (ii) policy mechanisms for curricular convergence and institutional integration, (iii) issues with teacher education and pedagogical training, and (iv) how multidisciplinary approaches align with employability, innovation, and lifelong learning. It examines how NEP 2020 promotes universities to become knowledge centres that support inquiry, adaptability, and creativity, particularly through the establishment of the Academic Bank of Credits (ABC), Multidisciplinary Education and Research Universities (MERUs), and a flexible choice-based credit system. In addition to incorporating global case studies from institutions that have successfully operationalized interdisciplinary learning, the paper draws on a qualitative thematic analysis of NEP 2020 documents, position papers, and recent reforms by the National Council for Educational Research and Training (NCERT) and the University Grants Commission (UGC). The results indicate that although the policy establishes a progressive framework, systemic adjustments in curriculum design, teacher competencies, governance, and infrastructure support are necessary for successful implementation.

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 Keywords

NEP-2020, Multidisciplinary, Credit based Structure

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Kaempferia rotunda, also known as ginger, is a medicinal plant that has been used for centuries in traditional medicine. It has a wide range of pharmacological activities, including anti-inflammatory, antioxidant, and anti-ulcerogenic effects. This study investigated the wound healing and ulcerogenic activity of ginger extract in rats. The results showed that ginger extract significantly promoted wound healing by increasing collagen deposition, angiogenesis, and epithelialization. It also inhibited the formation of gastric ulcers induced by ethanol and aspirin. These findings suggest that ginger extract has potential as a therapeutic agent for wound healing and ulcer prevention.

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 Keywords

Kaempferia rotunda Ginger Medicinal plant Wound healing Ulcerogenic activity Anti-inflammatory Antioxidant Anti-ulcer Collagen deposition Angiogenesis Epithelialization Ethanol-induced ulcers Aspirin-induced ulcers Therapeutic agent Traditional medicine

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The present study focuses on the formulation and evaluation of a herbal pain relief balm incorporating Tridax procumbens, a plant traditionally known for its anti-inflammatory and analgesic properties. The balm was prepared using a suitable base comprising natural waxes and oils, into which the extract of Tridax procumbens was incorporated in varying concentrations. The formulations were evaluated for physicochemical properties such as appearance, spreadability, pH, viscosity, and stability. The results indicated that the formulation containing optimal concentration of Tridax procumbens showed significant pain-relieving effects with good stability and acceptable organoleptic properties. This study supports the potential of Tridax procumbens as a natural alternative for topical pain management.

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 Keywords

Tridex procumben , pain relief , analgesic property , topical treatment , herbal balm.

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The situation that typically arises when we hear the term "predatory pricing" is one of a wealthy industrial giant. setting a product's price absurdly low in an effort to suppress rivals and establish a monopoly in the market. However, appearances can be misleading. Because it is sometimes clear that even a smaller organisation could fend against a cartel of larger entities by creating low price tags, predatory pricing is like a "double edged sword." However, the development of algorithmic predation has increased complexity and hardship for consumers as well as smaller companies. There is broad consensus among scientists working on artificial intelligence, a nascent technology whose growth pattern and consequences are yet unclear, that unless it is appropriately regulated with broad guidelines and rules, it would turn into a Frankenstein monster. Competition law faces a difficult problem with algorithmic pricing that necessitates a worldwide and cooperative response leaning towards the widely held belief that the situation will only get worse in the absence of a regulatory framework. Without considering the possible drawbacks that oligopolies and monopolies can experience as a result of algorithmic pricing, the study looks at India's competition laws. First, it will examine the fundamentals and workings of algorithmic pricing, with particular focus on the price models that big businesses are reportedly using, as well as how they might affect market dynamics. In order to detect threats in these systems and reduce their negative effects, which fall under a limited concept of recoupment stages, it is essential to recognise that oligopoly collisions are profitable even during predatory pricing periods.The potential illegal monopolisation required to outperform all other market participants is being overused under the guise of "AI." The study will look into the possibility of abusing algorithmic pricing in order to restrict some groups' access to the market or to set prices in a discriminatory manner. The study attempts to encourage the ethical and responsible application of AI in the marketplace by analysing both the anticipated and unanticipated effects of these technologies--which may result in further behaviour that endangers customers and competitors.

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 Keywords

Artificial Intelligence, Predatory pricing, Algorithmic pricing, competition law, collusion, Algorithmic Collusion, Automatic Pricing, Explicit Collusion and Tacit Collusion.

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This research investigates the recruitment challenges faced by Buzzworks Pvt. Ltd., Chennai, in hiring blue- and grey-collar workers within the business consulting and services sector. Focusing on issues like skill shortages, high attrition, and shifting workforce expectations, the study evaluates the effectiveness of current hiring practices and the use of digital tools. It also considers external factors such as labor laws and supply-demand gaps, offering practical recommendations for improvement. Data was gathered using a descriptive research design with purposive sampling from 132 recruiters, supported by secondary sources. Key findings reveal the continued reliance on traditional methods like referrals, alongside digital platforms, and stress the need for stronger communication, training partnerships, and improved engagement strategies to bridge the skill gap and enhance retention.

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 Keywords

Recruitment Challenges, Blue-collar Workforce, Grey-collar Employees,

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This study explores the phenomenon of employee turnover intention and its impact on organizational performance. Turnover intention, defined as an employee's conscious and deliberate willfulness to leave the organization, poses a significant challenge for organizations striving to retain talent and ensure operational efficiency. The research examines key influencing factors, including job satisfaction, organizational commitment, work environment, and career development opportunities. A structured questionnaire was administered to a randomly selected sample of 191 employees, and data were analyzed using SPSS software. Drawing on both qualitative and quantitative data, the study reveals that high turnover intentions can lead to reduced productivity, increased recruitment and training costs, and lower employee morale. The findings underscore the need for strategic human resource practices to mitigate turnover risks and foster workforce stability. The study concludes with practical recommendations for improving employee retention and sustaining organizational performance.

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 Keywords

Employee Turnover Intention, Organizational Performance, Human Resource Practices.

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This research is an in-depth examination of five naturally made herbal teas: aparajita (Clitoria ternatea), ginger (Zingiber officinale), Tulsi (Ocimum sanctum), mint (Mentha species), and a combination of Tulsi-mint (50:50). Physicochemical characterization identified unique characteristics among samples, which had pH ranges of 5.8-7.2, electrical conductivity of 580-900 ?S/cm, and different turbidity corresponding to their specific compositional factors. Phytochemical profiling disclosed signature bioactive markers--anthocyanins and teratins in aparajita, gingerols and shogaols in ginger, eugenol and rosmarinic acid in Tulsi, and menthol with flavonoids in mint--directly corresponding to their noted antioxidant activities. The mixture of Tulsi and mint showed favourable synergistic activities, with increased antioxidant activity over predicted additive values of single herbs. Structure-activity relationship analysis of the compounds identified ortho-dihydroxy configurations and conjugation extension in phenolic systems as key factors responsible for maximal free radical neutralization activities. These results support the scientific rationale underlying traditional uses of these herbal teas and propose their potential incorporation into contemporary preventive healthcare strategies for management of cognitive function, gastrointestinal health, stress, and metabolic control through their complementary mechanisms of action against oxidative stress and inflammatory processes.

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Keywords: Phytochemical profile, Antioxidant activity, Herbal synergy, Physiochemical property, Therapeutic potential

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Immediate Release Tablets (IRTs) are pivotal in pharmaceutical formulations, designed to disintegrate rapidly and release their active pharmaceutical ingredients (APIs) swiftly upon administration. This formulation approach ensures rapid onset of action, enhancing therapeutic efficacy, particularly in acute conditions. Advancements in excipient technology have significantly improved IRT performance. The incorporation of superdisintegrants such as sodium starch glycolate, croscarmellose sodium, and crospovidone has been shown to enhance the disintegration and dissolution rates of tablets, thereby improving bioavailability. Additionally, the use of co-processed excipients has optimized tablet hardness and friability, contributing to better tablet integrity and patient compliance. Formulation strategies, including the direct compression method, have been employed to streamline the manufacturing process of IRTs, reducing production costs and time. This method has been successfully utilized in the development of various IRTs, such as those containing valsartan, demonstrating satisfactory dissolution profiles and stability. Therapeutically, IRTs have proven beneficial in the management of conditions requiring rapid drug action, such as hypertension and acute pain. For instance, immediate release formulations of telmisartan have shown improved dissolution rates and bioavailability compared to conventional formulations.

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Immediate Release Tablets, Superdisintegrants, Direct Compression, Formulation Strategies, Therapeutic Impact, Bioavailability, Drug Dissolution, Pharmaceutical Excipients.

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