Volume 13 | Issue 11 |

 Abstract

Forensic odontology plays a crucial role in human identification through the examination of dental evidence, and orthodontics contributes significantly to this field by providing detailed, individualized records essential for forensic investigations. Orthodontic documentation including study casts, radiographs, and treatment notes preserves unique dental and craniofacial characteristics that remain reliable even under adverse conditions. These records facilitate accurate age and sex estimation, radiographic superimposition, and ante-mortem/post-mortem matching. Cephalometric analyses and dental arch measurements reveal sexual dimorphism, while age estimation techniques such as Demirjian's and Cameriere's methods enhance forensic precision. Orthodontic appliances serve as durable physical identifiers, particularly valuable in mass disaster victim identification (DVI). Advances in digital orthodontics, including CBCT and AI-based morphometric analysis, have further improved forensic accuracy. Thus, orthodontics bridges clinical documentation and legal identification, reinforcing its indispensable role within modern forensic odontology.

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Forensic Odontology, Orthodontic Records, Age Estimation, Sex Determination, Mass Disaster Identification

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Keywords: Moral Injury, Secular Buddhism, Mindfulness, Compassion, Procedural Justice, Preventive Intervention, Equanimity, Ethical Decision-Making, Guardian Mindset.

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Physico-chemical Analysis of a coal mines area of Parasia city (M.P.), India in month of April, 2022. Water samples were collected from Four different sites namely (S1)- discharge water Sethiya mine, (S2)- Setting tank Sethiya mine, (S3) Old quarry Sethiya mine, (S4)- Pench river Sethiya village. The range of observations are as under; Temperature 24-320 C, pH of water ranges between 7.1 to 7.2, Cl from 35-75.5 ppm, Nitrate from 1.3-2.5 ppm, Fluoride from 0.43-0.87 ppm, Calcium hardness from 125-152 ppm and Magnesium hardness from 60-76 ppm and TDS from 255-499 ppm. Regular monitoring of water quality is necessary to have a check on surface water quality for the sake of human life & to maintain a balanced aesthetical value of religious.

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Physico-chemical Analysis ,Water quality and Water resources etc.

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Financial planning plays a vital role in achieving financial stability and long-term wealth creation. One of the key components of financial planning is tax-saving investment, which allows individuals to optimize their income while contributing to future financial goals such as education, retirement and wealth creation. This study aims to assess the level of financial planning and awareness among individuals regarding various tax-saving investment products such as Public Provident Fund (PPF), National Savings Certificate (NSC), Equity Linked Savings Scheme (ELSS), life insurance, Pradhan Mantri Vaya-Vandana yojana (PMVVY), Sukanya Samruddhi yojana (SSY) and pension schemes under Section 80C of the Income Tax Act. The research paper seeks to identify the extent of awareness, the factors influencing investment decisions, and analyse the preference of tax saving investment options of the respondents. Primary Data will be collected through structured questionnaires and analyzed to understand the relationship between demographic variables and investment behavior. The findings of this study are expected to provide insights into the current state of financial literacy, highlight gaps in awareness, and suggest measures to promote informed decision-making in tax-efficient investments.

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 Keywords

Financial planning, Tax-saving investments, Financial awareness, Financial literacy

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In today's fast-paced digital era, the Information Technology (IT) sector standsas one of the most dynamic and demanding industries globally. With the ever-evolving technological landscape and relentless project deadlines, IT employees often find themselves subjected to high levels of stress. Recognizing the critical importance of employee well- being,organizationsareincreasinglyturningtoinnovativesolutionstomonitorandmanage stress levels among their workforce. In this context, the integration of machine learning techniques with live face monitoring using image processing, particularly through MATLAB, presents a promising avenue for stress detection and mitigation. Machine learning algorithms offer a powerful toolset for analysing complex data patterns and extractingactionableinsights. Byleveragingthesealgorithmsinconjunctionwithlivefacemonitoring, psychological states in real-time. Through the analysis of facial expressions, physiological signals, and other relevant indicators, such systemscan provide valuable feedback on individuals' stress levels, enabling timely interventions and support mechanisms. By implementing stress detection systems based on machine learning algorithmscapturelivefacemonitoringusingthecameraofthesystem,wecollectthefacial expression ofthe employee for a particular time period. Further, pre-process the collected imageand extractthe featuresand fineturningtheimage capturedusingRegion ofInterest (ROI)model. Movingontonext step,processtheextracted featuresbyusingclassification ML algorithm like Random Forest and Light GBM to classify the captured image among the given category of emotions. It will display theresult by voiceand notification will pop up on the screen. The integration of machine learning with live face monitoring using image processing and MATLAB represents a transformative approach to stress detection and management in the IT

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MACHINE LEARNING ALOGRITHM RANDOM FOREST ALGORITHM SUPPORT VECTOR MACHINE

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In the contemporary landscape of hybrid work and digital transformation, understanding the key levers of employee engagement is critical for organizational success. This study empirically investigates the impact of four contemporary organizational drivers--Hybrid Work Autonomy, AI-Enabled Work Design, Personalized Career Growth, and Perceived Organizational Purpose (ESG)--on employee engagement. A quantitative research design was employed, utilizing a structured online questionnaire to collect data from 120 employees across technology, finance, and professional services sectors. Data were analyzed using descriptive statistics, reliability analysis, and multiple linear regression in SPSS. The findings reveal a clear hierarchy of influence among the drivers. Personalized Career Growth emerged as the most potent and statistically significant predictor (? = .462, p < .001), followed by Perceived Organizational Purpose (? = .266, p < .001) and Hybrid Work Autonomy (? = .187, p = .009). Contrary to expectations, AI-Enabled Work Design did not show a statistically significant unique contribution to engagement (? = .129, p = .066) when controlling for other factors. The overall regression model was highly significant (p < .001), explaining 59.5% of the variance in engagement. The study concludes that while flexibility and technology provide important foundational elements, they are secondary to deeper psychological factors of growth and purpose. It is recommended that organizations strategically prioritize personalized career development systems and authentically embed ESG principles into their culture. Furthermore, AI implementation should be reframed around human-AI collaboration and effective change management. This research provides a validated, hierarchical framework to help leaders allocate resources effectively to cultivate a sustainably engaged workforce.

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Employee Engagement, Hybrid Work, AI in HR, Career Development.

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Migration to the Gulf has been one of the most transformative socio-economic movements in modern Kerala's history. Beginning in the 1970s, this migration reshaped the state's economy, family structures, and collective imagination. Malayalam cinema is an art form deeply embedded in Malayali social consciousness and it has continuously engaged with the figure of the Gulf Malayali, portraying him as a symbol of aspiration, alienation, and nostalgia. This paper examines the cinematic representation of Gulf migration in Malayalam films, tracing its evolution from early idealized portrayals to recent introspective and critical narratives. Through close readings of the movies Arabikatha (2007), Pathemari (2015), and Aadujeevitham (2024) the study explores how Malayalam cinema visualizes the emotional, ideological, and cultural dimensions of migration and nostalgia. Hence the study explores to constructing a collective memory of the migrant experience in Kerala.

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Keywords- Migration, Nostalgia, Malayalam Cinema, Gulf Malayali, Diaspora, Cultural Identity

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India is a land of varied cultures, customs and rituals. Festivals are an integral part of the day to day lives of the Indian diaspora whether they live in India or outside. This blend of cultures, customs and rituals blend together and are celebrated as major junctions throughout the year in the form of festivals. These festivals are carriers, of messages and meanings. Amongst many, this paper highlights and significant features of environmental communication and behavioral change that prevail through various festivals in India. The environmental communication through festivals is not limited to sharing information, it is a symbolic, participatory, and experiential bundle that significantly nudges the way how individuals relate to nature. By blending the Environmental Communication Theory, Cultural Semiotics and Behavioral Sciences, this study proposes a conceptual framework for understanding how festivals communicate ecological values. This framework elicits rituals and their symbols, increased engagements in local communities and normalizing sustainable practices resulting in habits all triggered through environmental communication through various festivals. By projecting Indian festivals from the context of eco-rituals globally, this study emphasizes their unique composition of faith, nature, and communal flourishing. The study concludes that Indian festivals such as Avla Navami promote shared meaning of environmental awareness through traditions and rituals and trigger behavioral change. It, festivals become everyday teachers of environmental responsibility--gentle, joyful, and deeply rooted in culture. They offer a decolonial alternative to purely technocratic or media-centric discourses of the environment, reminding us that ecological custodianship can also be rooted in cultural continuity, feeling, and shared aesthetic experience. The future of environmental communication, it suggests, may depend as much on what we celebrate together as on what we legislate or campaign for.

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Environmental communication; Indian festivals; cultural semiotics; ritual studies; behavioral change; sustainability communication; collective flourishing

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Artificial Intelligence (AI) has emerged as a disruptive and potentially transformative force in modern healthcare, promising significant enhancements in clinical efficacy, operational efficiency, and personalized care delivery. This systematic review investigates the current state of AI implementation across diagnostics, drug discovery, and administrative functions, analyzing both the quantitative impacts and the crucial socio-technical challenges surrounding its adoption. AI systems, particularly deep learning architectures like Convolutional Neural Networks (CNNs), have demonstrated exceptional performance in specific clinical tasks, such as diagnostic imaging analysis, enabling interpretation of chest X-rays for critical conditions in under 10 seconds and reducing Magnetic Resonance Imaging (MRI) scanning times by 30% to 50%. These efficiency gains contribute substantially to optimizing system throughput.[1, 2] Economically, AI-driven remote patient monitoring is projected to save the healthcare industry $200 billion annually by 2028, while predictive systems generate savings of up to 30-45% in high-cost episodes like oncology care.[3, 4] However, successful scaling is hampered by pervasive issues of algorithmic bias, model generalizability (with performance sometimes dropping 20% on external datasets [5]), and the lack of Explainable AI (XAI) in real-world clinical settings. Furthermore, general-purpose generative AI models currently exhibit an overall diagnostic accuracy of only 52.1%, performing significantly worse than expert physicians.[6] The future trajectory of AI integration hinges upon the adoption of privacy-preserving architectures, such as Federated Learning, and advanced personalization techniques, including Digital Twin technology, guided by robust regulatory frameworks like Good Machine Learning Practice (GMLP) .

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Artificial Intelligence, Healthcare Systems, Machine Learning, Deep Learning, Diagnostic Imaging, Clinical Decision Support Systems (CDSS), Algorithmic Bias, Explainable AI (XAI), Digital Twins, Federated Learning.

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In the digital era, individuals increasingly rely on mobile applications to handle financial tasks; however, many struggle with fragmented systems that require manual entry and provide limited insight. This paper reviews two IEEE research works,:"Unveiling Financial Insights: The Daily Expense Tracker System Approach" and "Expense Management System"and proposes MoneyMate, a smart, automated mobile platform for expense tracking and budgeting. The system integrates machine learning and data visualization to offer users a simplified view of their spending habits, while maintaining privacy and security. This paper discusses the literature, methodology, results, and future work of MoneyMate as a research-oriented mini-project under VTU.

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Personal Finance, Expense Tracking, Budget Management, Data Analytics, Mobile Application.

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