Category Archives: Uncategorized

Authors: Arsath Mohamed M, Gokul M, Rajamanikandan R, Mr.M.Premkumar

Abstract: Manual attendance recording consumes classroom time and may permit proxy attendance. Face-recognition-based attendance systems can automate identity matching, but their reliability may be affected by illumination, image quality, and presentation attacks. This paper presents ATTENDAI, a webbased student attendance system designed to combine face recognition, voice verification, and eye-blink liveness detection in a staged verification workflow. The proposed implementation uses Python and Flask for application services, OpenCV with Haar Cascade face detection and Local Binary Patterns Histograms(LBPH) for face processing, Mel-Frequency Cepstral Coefficients (MFCC) for voice features, and facial landmarks with the Eye Aspect Ratio (EAR) for blink detection. Attendance is recordeonly after the configured verification stages succeed. The system also supports Admin, Staff, and Student roles, departmentwise management, attendance reporting, and a four-hour session rule intended to prevent duplicate entries while retaining historical records. This paper describes the motivation, system architecture, principal modules, session logic, and an evaluation plan. Quantitative performance results are not claimed because they must be obtained from controlled testing of the completed implementation.

DOI: https://doi.org/10.5281/zenodo.23337736

Published by: vikaspatanker

Authors: Assistant Professor G. Shalom

Abstract: Science fiction has long served as a platform for exploring alternative forms of existence, consciousness, and identity. In contemporary science fiction, the concepts of posthuman identity and alien consciousness have emerged as significant themes that challenge traditional human-centered perspectives. This study examines how science fiction narratives transcend biological, cultural, and technological boundaries to imagine new forms of subjectivity and coexistence. Drawing upon posthuman theory, cultural studies, and science fiction criticism, the research investigates the representation of alien consciousness and its role in reshaping understandings of identity, agency, and ethical responsibility. The study employs qualitative thematic analysis of selected contemporary science fiction novels, films, and television series. Particular attention is given to narratives that depict interactions between humans, artificial intelligences, extraterrestrial beings, and hybrid entities. The findings reveal that posthuman identity is frequently portrayed through the dissolution of conventional distinctions between human and non-human life forms. Alien consciousness functions as a narrative mechanism that challenges anthropocentric assumptions and encourages readers to reconsider the nature of intelligence, communication, and moral value. Results indicate that themes of identity transformation (35%), alien consciousness (25%), technological integration (20%), ethical coexistence (12%), and collective futures (8%) dominate contemporary science fiction. These themes reflect broader social concerns regarding technological advancement, environmental interconnectedness, and global diversity. The narratives examined emphasize empathy, adaptation, and collaboration as essential strategies for navigating increasingly complex forms of existence. The study concludes that science fiction provides a critical framework for understanding posthuman futures and the ethical implications of encounters with radically different forms of consciousness. By imagining worlds that extend beyond traditional human boundaries, contemporary science fiction encourages new perspectives on identity, coexistence, and the future evolution of intelligent life. These narratives contribute significantly to ongoing debates concerning humanity’s place within an interconnected and technologically mediated universe.

DOI: https://doi.org/10.5281/zenodo.23335984

Published by: vikaspatanker

Authors: Associate Professor Dr G. Kokila Selva Kumari

Abstract: Chemistry education presents distinctive pedagogical challenges because learners must interpret observable phenomena, infer processes occurring at the molecular and atomic levels, and represent these processes through chemical symbols, equations, and models. Conventional instructional approaches do not always provide sufficient opportunities to integrate these different forms of representation or to engage in repeated, exploratory experimentation. Immersive virtual environments offer an alternative learning space in which students can manipulate three-dimensional molecular structures, investigate chemical reactions, rehearse laboratory procedures, and collaborate in simulated scientific settings. This article reveals the educational potential of metaverse-enabled chemistry education through a thematic synthesis of published research on virtual reality (VR), augmented reality (AR), and virtual chemistry laboratories. The discussion is organised around five major themes. The first explores how immersive virtual environments help students visualise molecular structures and understand chemical concepts through different representations. The second examines how virtual experiments provide opportunities for hands-on-style learning, exploration, and scientific investigation. The third focuses on the role of virtual environments in developing laboratory safety awareness and understanding experimental procedures. The fourth considers how these technologies can promote student interest, active participation, teamwork, and collaborative learning. The fifth discusses the practical and ethical challenges of implementing these technologies, including teaching methods, data privacy, accessibility, equipment availability, and infrastructure requirements. Existing evidence indicates that immersive technologies can support selected learning outcomes, even though their effectiveness varies according to instructional design, learning objectives, learner characteristics, and the comparison method employed. Research comparing virtual and physical chemistry laboratories also suggests that virtual environments can support aspects of conceptual learning and procedural practice, but they do not automatically reproduce all the behavioural demands of laboratory work. The article therefore advances a pedagogically integrated model in which immersive environments complement physical experiments, guided inquiry, teacher facilitation, and evidence-based assessment. It concludes that the educational value of the metaverse depends less on technological novelty than on its capacity to make chemical phenomena intellectually accessible, experimentally meaningful, and educationally inclusive.

DOI: https://doi.org/10.5281/zenodo.23334490

Published by: vikaspatanker

Authors: Kosisochukwu Henry Ukpabi, Abdullahi Mohammed Ibrahim, Zainab Abdulsalam Jamilu

Abstract: Small and medium-sized enterprises (SMEs) operating in perishable food supply chains face intertwined operational and financial risks: inventory can deteriorate before sale, postharvest losses reduce cash available for repayment, and many firms have thin or irregular formal credit histories. This study proposes a leakage-aware, explainable artificial intelligence (AI) framework that integrates food shelf-life, postharvest-loss, commodity-price, and digital banking features to assess credit risk for Nigerian perishable-food SMEs. Because linked Nigerian lender-level repayment data and firm-level shelf-life measurements were not available for this research, the empirical demonstration uses a clearly labelled dataset rather than claiming results from real borrowers. A reproducible simulation of 5,000 SME-loan observations was specified, with 70%/15%/15% chronological train/validation/test partitions, a financial-only baseline, and an integrated model using LightGBM-style gradient boosting. Logistic regression and random forest were included as benchmarks; SHAP-style feature attribution was used for interpretability. The simulated results illustrate the intended evaluation, not observed Nigerian banking performance: the financial-only baseline achieved a test ROC-AUC of 0.742 and PR-AUC of 0.356, while the integrated model achieved ROC-AUC 0.801 and PR-AUC 0.421. At a threshold selected on validation data, recall increased from 0.61 to 0.70, while Brier score improved from 0.176 to 0.158. The largest simulated contributors were recent repayment behaviour, cash-flow volatility, estimated remaining shelf life, postharvest-loss rate, and debt-service coverage. A random split produced more optimistic estimates than chronological evaluation, demonstrating why time-aware validation is essential. The main contributions are (i) a domain-specific framework linking food deterioration to credit risk, (ii) a leakage-control protocol for temporal financial data, (iii) an explainability and calibration evaluation plan, and (iv) a transparent synthetic benchmark that can be replaced by real data. These results are illustrative only; empirical conclusions require validation using consented, anonymised lending outcomes and measured food-quality data.

DOI: https://doi.org/10.5281/zenodo.23333454

Published by: vikaspatanker

Authors: Abubakar Mairiga, Naveed Anwar, Biddy Casselden

Abstract: Mobile applications for tinnitus management have proliferated rapidly, yet their real-world adoption remains strikingly low. A mixed-methods study, combining sentiment analysis of 13,096 user reviews from 42 tinnitus applications, a cross-sectional survey of 171 adults with self-reported tinnitus, and in-depth semi-structured interviews with 19 participants, was conducted to investigate the socio-demographic and systemic barriers that prevent diverse populations from adopting these tools. Only 8.6% of survey respondents reported active app use despite the availability of 42 identified applications. Chi-square tests confirmed no statistically significant association between app adoption and either age (χ² = 6.25, df = 4, p > .05) or gender (χ² = 0.42, df = 4, p > .05), indicating that barriers are systemic rather than demographic. A point-biserial correlation demonstrated a very strong positive relationship between app use and subjective well-being (rpb = 0.82, p < .001). Contrary to stereotypes, adults aged 30-49 years and full-time employed professionals constituted significant proportions of app users, challenging the assumption that tinnitus apps are used primarily by elderly retirees. Five principal barriers were identified through thematic analysis: low awareness and absent clinician referral pathways, lack of marketplace quality standardisation, limited personalisation, digital literacy challenges for older users, and privacy and data security concerns. Actionable recommendations are proposed for developers, clinicians, and policymakers to create user-centred, inclusive digital interventions that close the efficacy-accessibility gap in tinnitus self-management.

DOI: https://doi.org/10.5281/zenodo.23332874

Published by: vikaspatanker

Authors: Aayesha Rahman

Abstract: This paper aims to discuss the debate across various social media platforms on the impact of “BookTok,” which is a side of TikTok dedicated to readers sharing their opinions, recommendations, reviews, and experiences with books. Many individuals and influencers have made a claim that during and after COVID-19, there has been a compromise on the quality of books to meet the demands of consumers, which has led to books being commodified. Critics find it problematic as new releases flood the market, and the characteristics such as longer writing period and meticulous editing process, are replaced by books that are written, edited, and published within the span of a year. The question that any reader should ask themselves is the outcome they get out of reading by this shift in literary standards.

DOI: https://doi.org/10.5281/zenodo.23338534

Published by: vikaspatanker

Authors: Mohammad Ali, Jin Xie, Wu Wenhuan

Abstract: The machine behind e-commerce recommendation systems is often based on Collaborative Filtering (CF) algorithms which are highly dependent on numerical star ratings ignoring the fact that user review text is a rich source of semantic information. This constraint increases the issue of data sparsity and lowers the quality of the recommendations. We suggest SA-BTM-CF, a Sentiment-Aware Collaborative Filtering system, which encompasses the Biterm Topic Model (BTM) with a conventional CF. The suggested methodology is a latent topic extractor of review literature and a fine-grained sentiment score generator of latent topic models which are employed to build an enriched user-item rating matrices. Personalized product suggestions are then created by computing user similarity on these sentiment-augmented ratings. Large scale shampoo review data on the JD.com site is experimented with and experimentally validates that SA-BTM-CF can be used to effectively reduce sparsity in data, and it can be used to obtain better recommendations than current baseline algorithms.

DOI: https://doi.org/10.5281/zenodo.23310790

Published by: vikaspatanker

Authors: Thoomula Kavya Sri

Abstract: The fusion of artificial intelligence (AI), data science, and cloud computing technologies is transforming the nature of the digital economy from disconnected technological silos to interdependent ecosystems that complement each other. This paper explores current trends within these interrelated fields such as world models, agentic AI systems, cloud-native AI integration, and industrialization of data science. Mixed methods of research including the systematic literature review combined with the quantitative analysis of industry data is suggested. Convergence patterns analysis shows that cloud platforms transform from mere infrastructure into smart services ecosystems, and data science changes from disconnected modeling into engineering practice. Comparative analysis shows that companies embracing integrated approach to cloud-AI-data management enjoy considerably lower training costs and reduced deployment timeframes. The conclusion is made about the challenges related to governance, skill development, and infrastructure sustainability that need addressing.

DOI: https://doi.org/10.5281/zenodo.23310822

Published by: vikaspatanker

Authors: Khushboo chandra, Dr. Harbansh dixit

Abstract: The incorporation of Artificial Intelligence (AI) in judicial processes is perhaps the greatest technological innovation which has impacted legal systems globally. In India, there has been an increasing trend among the judicial systems towards adopting new technologies in order to increase efficiency, transparency, accessibility, and administration of justice. With the incorporation of technologies like e-Courts, virtual court sessions, electronic case management systems, and AI-enabled legal research tools, the groundwork has been laid for a technology-driven mechanism for administering justice. However, AI has not been adopted to replace judicial decision-making process in India but has been used to assist judges, lawyers, researchers, and court staff in performing monotonous and data-intensive tasks. These trends have become even more pertinent considering the huge number of pending cases and increasing need for justice.The present work will discuss how the use of AI has evolved in the Indian judicial system by considering the technological advancements made so far, judicial reforms, legal issues arising therefrom and possible future scenarios. The study will explore the benefits and risks associated with the use of AI in improving judicial efficiency in India. This study will adopt a doctrinal approach to qualitative research through constitutional provisions, court judgments, policies, government reports, and scholarly work. It contends that AI should only be viewed as assistive technology and not as something that should replace human judges.

DOI: https://doi.org/10.5281/zenodo.23279967

Published by: vikaspatanker

Authors: Ms. Tejaswini Angre, Aryan Dass, Dev Thakker, Nirvaan Shah, Priyansh Jain, Tanya Prabhakar

Abstract: Operations Research (OR) is a scientific and analytical approach used to solve complex problems and support effective decision-making in real-life situations. It applies mathematical models, statistical techniques, optimization methods, and computational tools to identify the best possible solutions under given constraints. Operations Research has a wide range of applications in various fields, including healthcare, transportation, supply chain management, manufacturing, finance, agriculture, and education. In healthcare, it helps optimize hospital resources and patient scheduling. In transportation, it assists in route planning, traffic management, and reducing travel costs. In industries, it improves production planning, inventory control, and resource allocation. Similarly, businesses use Operations Research to minimize costs, maximize profits, and improve overall efficiency. This study explores the practical applications of Operations Research in real-life scenarios and highlights its importance in solving problems, utilizing resources efficiently, and improving organizational performance. The application of Operations Research enables individuals and organizations to make informed, data-driven decisions and achieve better outcomes in an increasingly complex and competitive environment.

DOI: https://doi.org/10.5281/zenodo.23276409

Published by: vikaspatanker