Volume 14 | Issue 4 |

 Abstract

Early disease risk prediction is essential for effective preventive healthcare. This paper presents an explainable multimodal machine learning framework that integrates clinical and lifestyle data for improved prediction accuracy. Models such as Logistic Regression, Random Forest, and Support Vector Machine are evaluated using metrics like accuracy and ROC-AUC. To enhance interpretability, SHAP is used to explain feature contributions. The results show that combining multimodal data with explainable AI improves both prediction performance and model transparency.

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 Keywords

Machine Learning, Multimodal Learning, Explainable AI, Healthcare Analytics, Disease Risk Prediction

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Creative Commons Attribution 4.0 and The Open Definition

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This study explores the intricate intersections of trauma, psychology, and poetic expression in the works of Christina Georgina Rossetti, with particular emphasis on selected poems that reflect emotional fragmentation, repression, and the negotiation of inner conflict. By employing a psychoanalytic and trauma-informed framework, the analysis foregrounds how poetic language becomes a site of both concealment and revelation, where desire, guilt, fear, and resilience are subtly encoded. The poems examined reveal a persistent tension between innocence and experience, bodily constraint and imaginative escape, as well as between spiritual aspiration and psychological unrest. Special attention is given to symbolic structures, recurring motifs, and the representation of female subjectivity, which together illuminate the poet's engagement with Victorian anxieties surrounding gender, morality, and emotional suppression. The study further interrogates how trauma manifests not only as thematic content but also as a shaping force within poetic form, rhythm, and imagery. Through close textual reading, the research demonstrates that Rossetti's poetry offers a nuanced portrayal of psychological struggle while simultaneously suggesting possibilities of healing and transcendence. Ultimately, this analysis contributes to a deeper understanding of the poet's oeuvre by situating her work within contemporary critical discourses on trauma and psychology, thereby opening new avenues for interpretation and scholarly engagement.

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 Keywords

Keywords: Trauma, Psychoanalysis, Victorian Poetry, Female Subjectivity, Symbolism, Psychological Conflict, Emotional Repression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The rapid proliferation of digital education platforms and remote learning environments has fundamentally transformed the way academic examinations are conducted worldwide. While online examinations offer unparalleled flexibility and accessibility, they simultaneously introduce a range of pressing challenges related to academic integrity, fairness, and institutional accountability. Traditional invigilation methods, which depend on physical presence and human observation, are wholly inadequate in virtual settings, necessitating the development of sophisticated, automated monitoring systems capable of operating at scale. This research paper presents a comprehensive Intelligent Examination Monitoring System (IEMS) that employs artificial intelligence, computer vision, and machine learning techniques to ensure secure, reliable, and tamper-resistant online examinations. The proposed system integrates facial recognition, multi-object detection, gaze tracking, and behavioral pattern analysis to monitor candidates in real time, identifying and flagging anomalies such as multiple faces in frame, prolonged absence from the camera view, presence of unauthorized devices or materials, and irregular movement patterns. The system architecture follows a modular, layered design comprising a responsive frontend interface, a robust backend server, and a dedicated AI processing engine. Experimental evaluations conducted across diverse testing scenarios demonstrate that the system consistently achieves accuracy rates between 93% and 96%, with low false positive rates and real-time response capabilities. These results underscore the system's viability as a scalable and practically deployable solution for modern educational institutions seeking to uphold examination integrity without disproportionate reliance on human invigilators.

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 Keywords

Keywords: Online Proctoring, Deep Learning, YOLOv8, Face Net, Behavior Analysis, Academic Integrity, Computer Vision.

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Son preference remains an important component to shape demographic trend and cultural reality in the country despite its socio-economic advancement. The research explores the prevalence, determinants, and consequences of son preference among residents of Nabadwip Municipality, West Bengal, through primary data collection from 100 participants. The adopted research methodology is a combination of qualitative and quantitative approaches, which include descriptive statistics, chi-square tests, odds ratios, and logistic regression analysis. The findings reveal a consistent but verities in dimension on son preference and related complex opinion of parents. While a majority (56%) favored balanced gender distribution in their family, 28% had a greater preference for male children, as also evidenced by the existing Child Sex Ratio of 909 girls to every 1000 boys. Education turns out to be the most important variable as higher education level tends to decrease gender bias. On the contrary, low socio-economic classes tend to exhibit son preference. Further, this research indicates that there is an influence of son preference on fertility practices such as delayed use of contraception and following the 'stopping rule'. Issues of lineage, old age security, and dowry continue to drive cultural influences in this regard. Although knowledge of gender equity programs is fairly high, their effects are rather minimal in terms of changing existing mindsets.

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 Keywords

Son Preferences, Gender equity, old age security, West Bengal.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Consumer preferences for quick commerce services are primarily shaped by convenience and speed, with most users valuing time-saving benefits. Digital accessibility through smart phones and high-speed internet fosters seamless adoption of on-demand platforms. User-friendly interfaces and simplified ordering processes enhance satisfaction and repeat usage. Youth demographics show stronger inclination, driven by lifestyle needs and influencer marketing. Trust in reliability and delivery accuracy remains critical for sustained engagement. Overall, quick commerce thrives on the intersection of technology, convenience, and evolving consumer expectations.

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 Keywords

Quick commerce, Consumer preferences, Consumer behavior, Ecommerce trends, etc.,

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Timely intervention during emergencies plays a decisive role in reducing mortality and morbidity, particularly within the "golden hour." Delays in professional emergency response services necessitate the development of community-based interventions. Community First Responders (CFRs) provide an effective solution by enabling trained citizens to deliver immediate assistance. This paper reviews the role of CFR systems, examines global best practices, and proposes an implementation framework for occupational and public health settings. Evidence suggests that early intervention significantly improves survival outcomes. Integration of CFR systems is essential for building resilient communities.

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Community First Responder, Emergency Preparedness, CPR, First Aid, Occupational Health, Public Safety

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Creative Commons Attribution 4.0 and The Open Definition

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This study examines the growing role of predictive analytics powered by Artificial Intelligence (AI) in transforming employee retention strategies within modern organizations. With rising employee turnover posing significant financial and operational challenges, companies are increasingly leveraging advanced HR analytics tools such as SAP SuccessFactors and Workday to anticipate and address attrition risks proactively. The research exploress how AI-driven models analyze employee data--including performance metrics, engagement levels, compensation patterns, and behavioral indicators--to identify potential turnover trends and enable data-driven decision-making.The study adopts a mixed-method approach, combining primary data collected through employee surveys and HR professional interviews with secondary data from existing literature and industry reports. It evaluates the effectiveness, accuracy, and practical implications of predictive analytics in reducing attrition rates and enhancing employee engagement. Additionally, the research highlights key challenges such as data privacy concerns, algorithmic bias, and organizational readiness for AI adoption.

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Predictive Analytics, Employee Retention, Data-Driven Decision Making

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Creative Commons Attribution 4.0 and The Open Definition

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This review article examines the existing state of Diversity, Equity & Inclusion (DEI) practices in Indian organizations, with particular emphasis on ground-level implementation metrics. Drawing from contemporary research and organizational practices, the study identified gap between policy frameworks and practical implementation of DEI initiatives across Indian corporate, public sector and social enterprises. The article synthesized existing literature, highlights measurement challenges and proposes a comprehensive framework for assessing DEI effectiveness through quantifiable ground-level metrics. Findings revealed that while Indian organizations adopt DEI policies, significant disparities existed in implementation, particularly concerning caste, gender, regional diversity and disability inclusion. The study recommends evidence-based metrics and accountability mechanisms to strengthen DEI outcomes in the Indian organizational context.

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Keywords: Diversity, Equity, Inclusion, Indian Organizations, DEI Metrics, Workplace Diversity & Organizational Justice.

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Creative Commons Attribution 4.0 and The Open Definition

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This paper offers a comparative analysis of Art Spiegelman's Maus and Marjane Satrapi's Persepolis, examining how both graphic narratives employ the conventions of the medium to document personal and familial histories situated within major twentieth-century upheavals, the Holocaust and the Iranian Revolution respectively. Drawing on Marianne Hirsch's concept of postmemory and Viktor Shklovsky's notion of defamiliarisation, the paper argues that both authors deploy the graphic novel not as a merely unconventional choice of form, but as a deliberate aesthetic and epistemological strategy. The visual grammar of the medium, anthropomorphic characterisation, minimalist line work, symbolic visual motifs, and the relationship between panel, gutter, and caption enables Spiegelman and Satrapi to negotiate the gap between lived experience and inherited trauma, and to establish forms of testimony and self-authorisation unavailable through conventional prose. The paper further explores how each author constructs a narrative avatar through non-photorealistic self-representation, at once personalising and universalising their accounts of oppression and loss. Dominant visual symbols such as the mouse in Maus and the veil in Persepolis are read as sustained reminders of the regimes against which both narratives bear witness. The paper concludes that the graphic novel form uniquely facilitates the recovery of suppressed or destroyed memory, and that both texts function simultaneously as acts of mourning, political resistance, and archival reconstruction.

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 Keywords

Graphic Narratives, Post Memory, Autobiography, Trauma, Graphic Novel

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Creative Commons Attribution 4.0 and The Open Definition

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The growing demand for faster and reliable deliveries has increased the importance of warehouse efficiency in third-party logistics (3PL) operations. This study analyses how Warehouse Management System (WMS) usage and manpower management influence on-time delivery performance in a multi-client warehouse environment. Operational data collected before and after process improvements, along with employee feedback, were used for the analysis. The results show that better workforce planning and improved coordination with WMS helped reduce processing delays and improve operational flow. After implementation, on-time delivery increased from 72% to 85%, while average processing time decreased from 30-40 minutes to 23-27 minutes. The study shows that warehouse efficiency depends not only on technology, but also on how effectively manpower is planned and utilized during daily operations.

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 Keywords

3PL Warehouse; Warehouse Management System (WMS); Operational Efficiency; On-Time Delivery (OTD); Manpower Management; Labour Productivity; Warehouse Operations; Process Optimization

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Creative Commons Attribution 4.0 and The Open Definition