Volume 14 | Issue 8 |

 Abstract

The digital transformation of higher education has expanded students' access to search engines, learning management systems, online courses, video resources, virtual meeting platforms, electronic scholarly resources and artificial intelligence applications. This study examines the pattern of digital tool usage and the major challenges faced by higher education students in using digital technologies for learning. The analysis is based on 564 responses collected from Higher education pursuing students from Coimbatore District. The Analysis shows that Google Search has the highest mean usage score, followed by SWAYAM/NPTEL) and Google Classroom. YouTube and AI Chat Bots share a mean of, while zoom/Google Meet and online libraries/e-journals record lower values respectively. The study also examines barriers measured on a five-point scale. The results reveal a strong preference for accessible and user-friendly digital resources, while scholarly e-resources and synchronous platforms are comparatively underused. The findings highlight the need to improve digital infrastructure, affordability, training, academic resource awareness and responsible technology use.

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 Keywords

Digital learning tools, higher education, SWAYAM, NPTEL, Google Classroom, AI chatbots, e-resources, digital barriers

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

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Hospitalized children; Anxiety; Pain perception; Structured play; Therapeutic communication; Pediatric nursing; Randomized controlled trial.

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Creative Commons Attribution 4.0 and The Open Definition

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Real estate plays a crucial role in the economy through its significant contribution to national GDP growth. Housing is the principal collateral and consumer commodity, serving as the largest fixed asset for families, which in turn influences their savings and consumption decisions. In the present paper, an attempt is made to offer conceptual order, investigate key topics, and recommend future research trajectories. The study analyses a sample of 805 journal articles from the Scopus database from 2016 to 2026 using a bibliometric analysis and a literature review. The article compiles a list of the top papers, authors, nations, organizations, and journals related to digital-based financial inclusion based on the Scopus database. The analysis was prepared using advanced Excel tools, RStudio, and VOSviewer. Networks of scientific publications, journals, researchers, institutions, nations, and phrases are constructed using VOSviewer. The study discovered that publication on this topic is continuously increasing. The writers with the most documents in this field include Gurran Nicole, Rowley Steven, Biswas Sujoy, Mukerji Arjun. Moreover, with 1780 papers, USA is the top-ranking nation in the field of digitally based financial inclusion. Sustainability International Journal of Housing Markets and Analy has published 55 papers in journals, making it the most sources in this field. Gurran, nicole and Rowley, steven receive the most co-citations. keyword analysis demonstrates the eight clusters that, combined with bibliographical coupling, aid in recognising the different streams of affordable housing market.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Housing Market, Bibliometric Analysis, Scopus, Scientific Mapping, Research Trends.

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Creative Commons Attribution 4.0 and The Open Definition

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Ian McEwan is a British author, dramatist, and one of the most well-known contemporary writers. He is best known for his award-winning novels, which have left a lasting influence on contemporary literature through their distinctive narrative style. His works have received six Booker Prize nominations and are widely admired for their elegance, precision, and exploration of complex human relationships and moral dilemmas. McEwan's ability to seamlessly combine psychological depth with social criticism distinguishes his fiction and makes his novels intellectually engaging through their exploration of the complexities of human experience. This paper focuses on literary techniques such as intertextuality, open endings, flashbacks, and metafiction by examining Ian McEwan's novels Atonement and Saturday.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Ian McEwan, literary techniques, intertextuality, open ending, flashback, metafiction.

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Creative Commons Attribution 4.0 and The Open Definition

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The behaviour of investors has an important role in determining the movement of stock prices. Traditional financial theories assume that investors make rational decisions and that market prices quickly reflect available information. However, actual market behaviour often shows that investors do not always respond to information in a rational manner. Two important behavioural patterns associated with this issue are overreaction and underreaction. Overreaction occurs when investors respond too strongly to new information, while underreaction refers to a delayed or insufficient response. Overreaction occurs when investors respond too strongly to new information. This can push stock prices away from their actual value and may lead to a later fall in prices. Underreaction is different. It occurs when investors respond slowly to new information, which may allow the price movement to continue for some time. This study examines evidence of overreaction and underreaction in selected Indian stocks of Sensex using a winner-loser portfolio approach. Weekly closing prices of 15 selected companies are used for the analysis. The five companies with the highest cumulative abnormal returns (CAR) are classified as winners, while the five companies with the lowest CAR are classified as losers. The BSE Sensex is used as the market benchmark. Abnormal returns are calculated using the market-adjusted return method. Average abnormal return (AAR) and cumulative average abnormal return (CAAR) are then used to examine the performance of the winner and loser portfolios. Five formation and testing periods are considered. These periods cover short, medium and long-term horizons. One-sample t-tests, paired-sample t-tests and Wilcoxon signed-rank tests are used to examine the significance of the results. The findings show mixed evidence. Negative Winner-Loser CAARs are found in three of the five testing periods. This shows that past winners performed worse than past losers in these periods and provides some evidence of overreaction. The strongest reversal is found in the medium-term period, with a Winner-Loser CAAR of -5.6658%. However, positive CAARs are found in the long-term period and one short-term period. These results suggest continuation and are consistent with possible underreaction. The findings therefore suggest that investor behaviour varies across investment horizons. The evidence of reversal and continuation indicates that both overreaction and underreaction may occur in the Indian stock market, but their presence is not consistent across all periods.

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 Keywords

Investor Behaviour; Overreaction; Underreaction; Behavioural Finance; Indian Stock Market; Investment Decision-Making, Price Reversal, Winner-Loser Effect.

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Creative Commons Attribution 4.0 and The Open Definition

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Trauma and empowerment continue to be themes of focus in modern women's writing, given the challenges of oppression, survival and transformation. Chika Unigwe's On Black Sisters' Street and Alice Walker's The Color Purple offer strong and interesting stories of women who suffer physically, emotionally and socially, who are trying to find themselves and their dignity. The novels, despite their distinct settings and time periods, show striking similarities in their depiction of gender discrimination, sexual violence, exploitation and the domination of men. This comparative reading explores how both writers portray trauma not as a victimization experience but as a transformative process that helps grant access to resilience, self-discovery and empowerment. The analysis also examines how the protagonists challenge oppressive structures, how they begin to construct themselves in a new way, and how they challenge society's norms and expectations that aim to silence them. The comparison of these two texts emphasizes the common experiences of women in different cultures and the timeless power of books to depict human strength, hope, and the struggle for freedom.

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Creative Commons Attribution 4.0 and The Open Definition

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Trauma, Empowerment, Women's Resilience, Identity, Patriarchy, Gender Oppression, Female Agency.

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Creative Commons Attribution 4.0 and The Open Definition

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The non-intrusive nature of face recognition and its broad range of applications in security, surveillance, access control, and identity verification systems have made it one of the most popular biometric technologies. The need for precise and effective real-time face recognition systems has grown dramatically with the quick development of digital imaging equipment, artificial intelligence, and embedded computing platforms. However, differences in lighting, position, facial expression, occlusion, and computing restrictions make it difficult to achieve high identification accuracy while meeting real-time requirements. A thorough analysis of real-time face recognition systems is given in this study, which covers both conventional and modern methods, publicly accessible datasets, performance assessment measures, and deployment issues. In addition to local feature-based approaches like LBP, HOG, SIFT, and their variations, the study methodically examines traditional appearance-based and statistical techniques like PCA, LDA, and ICA. The contributions and limits of key-point descriptors and correlation filter-based techniques in real-time settings are also examined. The study also addresses the shift to deep-learning-based facial recognition models, with a focus on resource-constrained and real-time systems that are light weight. The size, annotation kinds, and appropriateness for real-time assessment of publicly accessible datasets that are often used for benchmarking face recognition systems are summarized. Along with the trade-offs between accuracy, speed, memory usage, and energy efficiency, this study also looks at the role of hardware acceleration employing CPUs, GPUs, and FPGAs. There is also discussion of important issues including scalability, privacy, security, and ethical issues. This study seeks to provide academics and practitioners a comprehensive knowledge of the present status of real-time face recognition and to suggest attractive avenues for future research by compiling recent developments and highlighting outstanding research concerns.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Real-Time Face Recognition; Face Detection; Computer Vision; Feature Extraction; Face Recognition Datasets; Performance Evaluation; Hardware Acceleration; Security and Surveillance

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Creative Commons Attribution 4.0 and The Open Definition

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Creative Commons Attribution 4.0 and The Open Definition

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Hospitalized children; Play-based intervention; Therapeutic communication; Anxiety; Pain perception; Recovery outcomes; Pediatric nursing; Randomized controlled trial.

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Creative Commons Attribution 4.0 and The Open Definition

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Movie production includes huge amount of financial risk, and investment decisions are frequently based on previous experience or market intuition rather than statistics. We propose a machine learning based methodology for predicting a movie's Return on Investment (ROI) based in information available before its release. Our proposed model considers budget, runtime, genre, director, production company, release timing and movie overview to estimate the expected ROI. Multiple machine learning models were compared, and Random Forest showed the best performance and it was selected as final prediction model. Then, we used SHAP (Shapley Additive exPlanations) to find and explain the factors that significantly impact each prediction. A Decision Support System (DSS) is developed to help producers estimate different production scenarios before making investment decisions. This allows the user to change important factors such as budget, runtime, franchise status and release timing and see how those changes affect the predicted ROI. Our system suggests an investment based on the estimated ROI and helps producers in making better investment decisions.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Movie ROI Prediction, Machine Learning, Random Forest, SHAP, Explainable Artificial Intelligence (XAI), Decision Support System (DSS), Return on Investment (ROI), Film Industry.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Emotional displacement, migration, trauma, family separation, Borderlands, divided identity, memory, belonging.

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Creative Commons Attribution 4.0 and The Open Definition