British Journal of Multidisciplinary Studies
type: channel
description: Description: The British Journal of Multidisciplinary Studies (BJMS) is a peer-reviewed, open-access academic journal dedicated to publishing high-quality research across all academic disciplines. BJMS provides a platform for scholars, researchers, and practitioners worldwide to share innovative ideas, methodologies, and findings, fostering interdisciplinary collaboration and advancing knowledge across sciences, engineering, social sciences, humanities, arts, health, and emerging fields. Aims and Scope: To publish original research, review articles, case studies, conceptual papers, short communications, and technical reports across all disciplines. To promote interdisciplinary research and dialogue between different academic domains. To disseminate research with practical, societal, and professional relevance. To uphold rigorous peer-review standards ensuring integrity, quality, and credibility of published work. Disciplines Covered: Natural Sciences: Physics Chemistry Biology Mathematics Statistics Earth and Planetary Sciences Environmental Science Astronomy and Space Science Material Science Geology Geography Meteorology Oceanography Agricultural Science Biochemistry Biotechnology Genetics Microbiology Ecology Zoology Botany Engineering and Technology: Mechanical Engineering Civil Engineering Electrical and Electronics Engineering Chemical Engineering Computer Science Information Technology Artificial Intelligence and Machine Learning Robotics and Automation Software Engineering Telecommunications Industrial Engineering Aeronautical and Aerospace Engineering Mechatronics Energy and Renewable Technologies Nanotechnology Materials Engineering Construction Engineering Medical and Health Sciences: Medicine Surgery Nursing Pharmacy Dentistry Public Health Biomedical Science Psychology Psychiatry Nutrition and Dietetics Physiotherapy Occupational Therapy Health Informatics Epidemiology Genetics in Medicine Clinical Research Veterinary Science Social Sciences: Economics …
publisher: Al-Kindi Center for Research and Development
language: en
publication name: British Journal of Multidisciplinary Studies
issn: 2978-8110
items: Digital Twin-Based Process Optimization and Defect Prediction in Metal Additive Manufacturing for Critical Mechanical Components
items: Predictive Analytics, Artificial Intelligence, and Machine Learning for Real-Time Nowcasting and Forecasting of Inflation Using High-Frequency Retail Price and Energy Market Data
items: Structured Elicitation Primitives for Reliable Multi-Agent Delegation and Recursive Planning
items: Artificial Intelligence and Predictive Machine Learning for Financial Fraud Detection, Cyber Risk Management, and Infrastructure Resilience in the U.S. Banking Industry
items: Event-Driven Intelligent ERP Architecture for Real-Time Enterprise Financial and Revenue Processing
items: GraphQL in Wealth Management Platforms: Optimizing Data Access and Performance
items: Legislative Miraculousness in the Holy Qur’an: A Study of the Concept, Significance, and Characteristics
items: “I Have a Plan”: A Critical Discourse Analysis of Political Messaging in Tarique Rahman’s London Farewell Speech
items: Laser-Engineered Retinoid Nanocarriers Mitigate Isotretinoin-Induced Hepatic Injury: A Multilevel Hematological, Physiological, Molecular, and Histopathological Study in Rats
items: The Impact of an Interactive English E-Book in Developing Active Listening Skills
items: The Heat Penalty: Evaluating the Compound Climate and Urban Heat Island Risks in Accelerated Megacity Development
items: Optimizing Vaccine Distribution Networks in Heterogeneous Populations Using Geospatial Data and Demographic Risk Models
items: Telemedicine Adoption and Health Equity: Evaluating Access, Quality, and Patient Outcomes in Low-Resource Settings
items: Consumer Trust in E-Commerce: The Role of Personalisation, Security, and Brand Authenticity
items: Digital Pedagogy in the Post-Pandemic Era: Opportunities and Inequalities in Higher Education
items: Urban Heat Islands and Climate Vulnerability: Assessing Risks in Rapidly Growing Megacities
items: From Automation to Augmentation: How Generative AI Is Reshaping the Global Workforce
items: The Rising Burden of Non-Communicable Diseases in South Asia: Challenges and Policy Pathways for Prevention
items: Artificial Intelligence as a Social Actor: Reconfiguring Power, Identity, and Agency in Contemporary Societies
items: Predictive Algorithms and Social Inequality: A Sociological Analysis of Bias, Governance, and Digital Surveillance
items: How Oracle Cloud Helps Enterprises Achieve True Cloud Sovereignty
items: Designing High Availability Architectures on Oracle Cloud Infrastructure (OCI)
items: Why Multicloud Is the New Normal

Digital Twin-Based Process Optimization and Defect Prediction in Metal Additive Manufacturing for Critical Mechanical Components
type: item
description: Digital twin technology has emerged as a promising route for improving process stability, traceability, and quality assurance in metal additive manufacturing, particularly for safety-critical and high-value mechanical components. This study presents a digital twin-based framework for process optimization and defect prediction in laser powder bed fusion (LPBF) of critical mechanical parts. The proposed framework integrates a process digital thread, in-situ sensing, a simplified thermal–physics model, and a machine-learning-based defect prediction module within a closed-loop optimization architecture. A representative Ti-6Al-4V load-bearing bracket is considered as a case study to demonstrate how the digital twin can monitor layer-wise thermal behavior, estimate defect probability, and recommend improved combinations of laser power, scan speed, hatch spacing, and layer thickness. The study further examines recent developments in digital twin implementation for metal additive manufacturing and shows that current research has progressed from static simulation toward real-time synchronization, sensor fusion, and quality-oriented architectures. However, important challenges remain in model transferability, standards integration, and component-level qualification. The proposed methodology addresses these issues by explicitly linking process parameters to key defect mechanisms, including lack of fusion, keyhole porosity, thermal distortion, and powder-bed irregularity. Illustrative calculations and representative numerical results indicate that the optimized parameter set can reduce predicted porosity, improve density and geometric stability, and maintain practical productivity. Overall, the study demonstrates the potential of digital twins to provide a more reliable and data-driven pathway for manufacturing critical components in aerospace, biomedical, and energy applications.
subject: Research Article
  topic: section
subject:
  topic: keywords
  value: Digital twin; metal additive manufacturing; laser powder bed fusion; defect prediction; process optimization; critical mechanical components; in-situ monitoring; machine learning; thermal modeling; quality assurance
creator: Md Arman Hossain
creator: Md Abdul Aziz Bhuiyan
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-03-17
publication date: 2025-03-17
starting page: 57
ending page: 72
doi: 10.32996/bjmss.2025.3.2.5

Predictive Analytics, Artificial Intelligence, and Machine Learning for Real-Time Nowcasting and Forecasting of Inflation Using High-Frequency Retail Price and Energy Market Data
type: item
description: Inflation forecasting became harder after the pandemic because price formation turned faster, more uneven, and more exposed to energy shocks, supply disruptions, and changes in household spending. This paper develops a framework for real-time nowcasting and short-horizon forecasting of U.S. inflation by combining predictive analytics, artificial intelligence, and machine learning with high-frequency retail price and energy-market information observed before official CPI release dates. The empirical design uses publicly available data, centered on BLS consumer price and average-price series and EIA daily and weekly energy prices. Monthly CPI inflation is linked to within-month signals from retail gasoline prices, electricity and utility-gas measures, weekly retail motor fuel prices, and daily crude-oil benchmarks. The modeling architecture integrates econometric benchmarks with elastic net, random forest, and gradient boosting models under pseudo-real-time evaluation. Results from the empirical illustration show that feature-rich machine learning models, especially penalized regression that controls overfitting while exploiting mixed-frequency signals, can outperform naïve and autoregressive benchmarks for 2023-2024 monthly nowcasts. The findings also indicate that gasoline and broader energy signals are most valuable when inflation is turning and when conventional lag structures respond too slowly. Beyond predictive gains, the paper contributes a transparent workflow for mixed-frequency feature engineering, model governance, and explainability. High-frequency inflation surveillance should not replace official statistics or professional judgment; it should complement them by offering earlier, more adaptive evidence for central banks, financial institutions, retailers, and policy analysts. Practical implications and future research directions for richer scanner and web-scraped price systems are discussed.
subject: Research Article
  topic: section
subject: Inflation nowcasting; inflation forecasting; machine learning; predictive analytics; artificial intelligence; consumer price index; energy prices; retail prices; mixed-frequency data; CPI
  topic: keywords
creator: Md Kamrul Islam
creator: Shah Farhan Rabbani
creator: Yusuf Oli Rahat
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by-nc/4.0
date: 2025-12-29
publication date: 2025-12-29
starting page: 44
ending page: 56
doi: 10.32996/bjmss.2025.3.2.4

Structured Elicitation Primitives for Reliable Multi-Agent Delegation and Recursive Planning
type: item
description: The transition of Large Language Models (LLMs) from passive information retrieval interfaces to agentic systems capable of multi-step execution represents a significant paradigm shift in artificial intelligence. However, the reliability of these agents is frequently compromised by stochastic drift, hallucination, and the inability to maintain coherent context over extended planning horizons. This paper proposes a theoretical framework for Reliable Agent Delegation (RAD), focusing on structured elicitation techniques that constrain the probabilistic output of foundation models into deterministic workflows. We analyze role assignment mechanisms, meta-reasoning prompts, and self-corrective failure recovery loops. Drawing upon existing literature in Chain-of-Thought (CoT) reasoning, ReAct frameworks, and formal verification, we posit that imposing rigid syntactic and semantic constraints on elicitation allows for verifiable delegation between orchestrator and worker agents. We discuss the security implications of such architectures, specifically regarding indirect prompt injection and cascading logic failures, and outline a methodology for constructing robust, self-healing agentic systems.
subject: Research Article
  topic: section
subject: LLM Agents, Elicitation, Automated Planning, Multi-Agent Systems, Robustness, Chain-of-Thought, Meta-Reasoning
  topic: keywords
creator: SUNIL KARTHIK KOTA
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by-nc/4.0
date: 2025-08-29
publication date: 2025-08-29
starting page: 38
ending page: 43
doi: 10.32996/bjmss.2025.3.2.3

Artificial Intelligence and Predictive Machine Learning for Financial Fraud Detection, Cyber Risk Management, and Infrastructure Resilience in the U.S. Banking Industry
type: item
description: The U.S. banking industry operates in a threat environment shaped by fraud convergence, cyber-enabled financial crime, third-party concentration, and rising operational interdependence across payment, cloud, and identity infrastructures. Traditional control architectures remain necessary, but static rules and siloed monitoring often react too slowly to adversaries that exploit speed, scale, and cross-channel coordination (Ngai et al., 2011; Abdallah et al., 2016). This paper develops a predictive analytics framework that links artificial intelligence, machine learning, and resilience-oriented governance to three objectives: earlier detection of financial fraud, adaptive management of cyber risk, and protection of banking operations. The study synthesizes approximately fifty academic and policy sources and grounds the framework in authentic public data released through 2024, including FBI Internet Crime Complaint Center statistics, FinCEN Bank Secrecy Act reporting data, OCC cyber-resilience guidance, FDIC risk analysis, and Federal Reserve supervisory material (Federal Bureau of Investigation [FBI], 2022, 2023, 2024a; FinCEN, 2023, 2024a; FDIC, 2024; OCC, 2024a). The paper argues that effective banking surveillance requires multimodal architectures combining transaction features, customer behavior, alert narratives, entity relationships, authentication telemetry, and external threat intelligence. It further shows that fraud prevention and cyber resilience should be treated as a unified problem because payment fraud, account takeover, business email compromise, ransomware, identity abuse, and third-party disruption increasingly share infrastructure, indicators, and institutional consequences. The proposed methodology integrates anomaly detection, graph analytics, gradient-boosted classification, natural language processing, and explainable governance dashboards within a risk-based operating model. Rather than claiming proprietary bank-level back-test results unavaila…
subject: Research Article
  topic: section
subject: Artificial intelligence; machine learning; banking fraud; cyber risk; operational resilience; suspicious activity reporting; graph analytics; anomaly detection
  topic: keywords
creator: Sakib Mahmud
creator: A S M FAHIM
creator: Md Moshiour Rahman
creator: Nusrat Jahan
creator: Md Ibrahim
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by-nc/4.0
date: 2025-11-27
publication date: 2025-11-27
starting page: 58
ending page: 77
doi: 10.32996/bjmss.2025.4.1.6

Event-Driven Intelligent ERP Architecture for Real-Time Enterprise Financial and Revenue Processing
type: item
description: Modern organizations increasingly function with digital ecosystems featuring high-frequency transactions, subscription-based revenue models, and dispersed application landscapes. Traditional ERP systems are based on synchronous processing and batch-oriented integration patterns that can lead to limited scalability, increased transaction latency, and delayed operational insights. Such limitations are especially noticeable in financial and revenue management contexts that rely on real-time responses to rapidly changing dynamics. This paper introduces a new Event-Driven Enterprise ERP Architecture (EDEA) that serves as the foundation for real-time transactions, continuous scalability, and independent automation on an enterprise level. While connecting tax sensors and other cloud-native microservices as well as event streaming services, the architecture leverages the extensibility capabilities of SAP S/4HANA to serve as the transactional backbone via SAP Business Technology Platform. The cloud application services are built with the SAP Cloud Application Programming Model, which allows modular microservice orchestration and an event-driven architecture. We propose a framework consisting of five architectural layers, namely Event Generation, Event Streaming Infrastructure, Microservice Processing Layer, Intelligent Automation Services and Enterprise Analytics. All these layers allow ERP systems to evolve from tightly coupled transactional engines into distributed event-driven ecosystems that can be leveraged in the real-time enterprise. Experimental evaluation of simulated enterprise workload processing up to 40 million business transactions per operational cycle. The findings show measurable increases in enterprise processing efficiency with 38% improvement in transaction throughput, 42% reduced latency to integrate systems, and 35% improved real-time revenue processing efficiency compared to standard synchronous ERP architectures. Model analysis for the performance of …
subject: Research Article
  topic: section
subject: Event-Driven Intelligent ERP Architecture; Real-Time Enterprise; Financial and Revenue Processing
  topic: keywords
creator: Raghavendra Depa
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-12-29
publication date: 2025-12-29
starting page: 20
ending page: 37
doi: 10.32996/bjmss.2025.4.2.2

GraphQL in Wealth Management Platforms: Optimizing Data Access and Performance
type: item
description: In regulated financial systems, such as wealth management platforms, it is necessary to have both a secure, compliant environment, as well as to provide users with real time portfolio analytics, and customizable dashboards. However, many traditional RESTful based API's require multiple round trips and pull down all the information requested from the server even if only some of it is needed; thus, resulting in significant delays when the system is at high volume usage levels. GraphQL allows for a single endpoint query model that is declarative in nature, where clients can ask for only what is needed. Previous studies have demonstrated how this model can significantly decrease the amount of data being transferred across the network and the number of network requests made when retrieving nested data [1]. The study reviews existing literature on empirical and theoretical studies that evaluate whether GraphQL is suitable for use in regulated financial environments. Included within this study’s evaluation are benchmarks, cost analysis research, and best practices for performance optimization, and security. Additionally, this study discusses how Federated GraphQL architecture can be used to create modular microservice architecture, as well as hybrid REST/GraphQL architecture. This study suggests that, for complex aggregation queries, GraphQL can reduce latency and backend requests by approximately one-half or more, improve developer productivity when governed properly, but must be weighed against the increased CPU usage seen in GraphQL resolvers when not optimized properly, and the need to implement proper security and compliance measures [2].
subject: Research Article
  topic: section
subject: GraphQL, REST, wealth management, API performance, microservices, query complexity, federation, security, compliance
  topic: keywords
creator: Ashmitha Nagraj
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2024-09-20
publication date: 2024-09-20
starting page: 16
ending page: 24
doi: 10.32996/bjmss.2024.3.1.3

Legislative Miraculousness in the Holy Qur’an: A Study of the Concept, Significance, and Characteristics
type: item
description: This research endeavours to illuminate an important feature of the poetry of Ibn Zaydon, namely the employment of an element of silent nature "the Moon", which is noted in his poetry in a striking manner worthy of study and reflection. The Moon in Arabic poetry has been present since today ' It has the characteristics of enabling the poet to express his psychological potentials, his relationship with himself and the other and all around him. This is what we clearly glimpse at Ibn Zaidon. The moon overlooks his debt here and there, bearing his emotional contradictions, his various experiences, such as his relationship with the beloved wallada Bint al-mustakfi, and the kings of al-Andalus, So we see him calling the moon sometimes for praise and for love and another time, and then for lamentation, for curse, and for glaciating the scourge of imprisonment sometimes another.....; So the research came to examine the above, and conclude that the recruitment mechanism, the motives for it, and its role in forming the text as a structure and meaning.
subject: Research Article
  topic: section
subject: Legislative miracles, Qur’anic rulings, justice, moral values, social organization
  topic: keywords
creator: Ali Azeez Neamh Al Mamouri
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2026-03-03
publication date: 2026-03-03
starting page: 22
ending page: 32
doi: 10.32996/jbmss.2026.4.1.3x

“I Have a Plan”: A Critical Discourse Analysis of Political Messaging in Tarique Rahman’s London Farewell Speech
type: item
description: This study conducts a Critical Discourse Analysis of Tarique Rahman’s London farewell speech, examining how political messaging, leadership construction, and ideological positioning are conveyed from exile. Using Fairclough’s three-dimensional model, the research analyzes linguistic choices, pronoun usage, modality, and rhetorical strategies to reveal how Rahman frames his political identity, promotes people-centered policies, and mobilizes support among the Bangladeshi public and diaspora. The speech emphasizes long-term planning, social welfare, and nationalistic vision, while deliberately avoiding confrontational rhetoric. Findings demonstrate that political discourse disseminated through digital media can extend influence beyond physical boundaries, legitimize authority, and shape public perception. This study underscores the effectiveness of Critical Discourse Analysis in uncovering power dynamics and ideological functions in contemporary Bangladeshi politics.
subject: Research Article
  topic: section
subject: Critical Discourse Analysis, Political Messaging, Exile Leadership, Bangladeshi Politics, Tarique Rahman
  topic: keywords
creator: Sultanul Arefin
creator: Md.Sadekul Islam
creator: Md. Jashim Uddin
creator: Marzana Binte Khan
creator: Maknun Binte Khan
creator: Mahamud Rafin
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by-nc/4.0
date: 2026-01-13
publication date: 2026-01-13
starting page: 10
ending page: 21
doi: 10.32996/bjmss.2025.4.1.2x

Laser-Engineered Retinoid Nanocarriers Mitigate Isotretinoin-Induced Hepatic Injury: A Multilevel Hematological, Physiological, Molecular, and Histopathological Study in Rats
type: item
description: Isotretinoin is an effective retinoid that is used as a treatment for severe acne, but its implementation is limited due to systemic adverse events, especially hepatotoxicity, which presents a challenge to clinical use. The current study was organized to examine the hematological, biochemical, molecular, and histopathological effects of isotretinoin on liver function in male rats, emphasizing the modulatory effect of laser-aided treatment. Forty adult male albino rats (8 experimental groups) were administered isotretinoin 20 mg/kg and 40 mg/kg orally at 24, 48, and 72 h time intervals over 30 days. Complete blood count analysis was done for the hematological parameters. Liver function was evaluated as serum alanine aminotransferase (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP). Molecular markers of liver injury, such as fatty acid–binding protein 1 (FABP1) and kallistatin, were analyzed by ELISA. Liver tissue histopathological evaluation was conducted with hematoxylin and eosin staining. It is demonstrated that significant dose- and time-dependent changes of hematological indices, including leukocyte imbalance and lower erythrocyte parameters and platelet variability, following isotretinoin treatment. The level of ALT, AST, and ALP were markedly elevated, suggesting hepatic insufficiency. Moreover, isotretinoin markedly increased the levels of FABP1 and decreased the levels of kallistatin, indicating hepatocellular injury and functional impairment of protection mechanisms. Histopathological findings indicated hepatocellular degeneration, vascular congestion, inflammatory infiltration, and sinusoidal dilatation that provided strong evidence of these biochemical and molecular alterations. Of interest, laser-associated treatment led to a marked decrease in isotretinoin toxicity (partial normalization of hematology), (reduction in liver enzyme activity, and) (modulation of FABP1 and kallistatin levels) and (enhancement of hepatic tissue architec…
subject: Research Article
  topic: section
subject: Isotretinoin; Laser-engineered nanocarriers; Hepatic injury; Physiology; Hematological parameters; FABP1; Kallistatin; Histopathology; Pulsed laser ablation in liquid (PLAL)
  topic: keywords
creator: Zainab Mohammed Abbas Hasson
creator: Halah Ali Abdulhussein Alsaleh
creator: Entidhar Jasim Khamees
creator: Safaa Mohammed Fadhel Abood Al Taee
rights: Copyright (c) 2026 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 01
ending page: 09
doi: 10.32996/bjmss.2025.4.1.1x

The Impact of an Interactive English E-Book in Developing Active Listening Skills
type: item
description: This study examines the impact of an interactive English e-book on the development of active listening skills among first-year female students in the Medical Health Track at the University of Bisha. Using a quasi-experimental design, (80 participants were randomly assigned to an experimental group (n = 40) and a control group (n = 40). The experimental group received instruction through an interactive English e-book, whereas the control group was taught using conventional instructional methods. Data were collected using pre- and post-tests assessing key components of active listening, namely auditory recall, listening comprehension, and auditory discrimination. The results indicate statistically significant improvements in auditory recall and listening comprehension among students exposed to the interactive e-book compared with those in the control group. However, no statistically significant differences were found between the two groups in auditory discrimination. These findings suggest that interactive English e-books can play an effective role in enhancing selected dimensions of active listening in higher education English language contexts. The study contributes empirical evidence to the literature on technology-enhanced language learning and underscores the pedagogical potential of interactive e-books for developing listening-related skills among university learners.
subject: Research Article
  topic: section
subject: Interactive English E-Book, Active Listening Skills, First-Year University Students, Technology-Enhanced Language Learning
  topic: keywords
creator: Hatim Mohamed Ahmed Osman
creator: Nouf Mohammed Faiz AlShahrani
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-12-29
publication date: 2025-12-29
starting page: 01
ending page: 19
doi: 10.32996/bjmss.2025.4.2.1

The Heat Penalty: Evaluating the Compound Climate and Urban Heat Island Risks in Accelerated Megacity Development
type: item
description: The rapid growth of megacities presents a critical challenge to climate resilience, as expanding urban footprints simultaneously intensify the Urban Heat Island (UHI) effect and increase population exposure to climate change impacts. This study assesses the compounded climate vulnerability resulting from the synergistic interaction between UHI intensification and extreme weather events in rapidly growing global megacities. Utilizing integrated methodologies that combine remote sensing of Land Surface Temperature (LST), spatial climate projections, and comprehensive socio-economic vulnerability indices, we map and quantify the areas of highest risk. Our findings demonstrate that UHI effects significantly amplify the magnitude and duration of heat stress events, translating to a heightened risk of morbidity and mortality, particularly in informal settlements and high-density, low-canopy zones. Crucially, the analysis reveals a disproportionate concentration of climate vulnerability among marginalized populations, where pre-existing socio-economic stressors intersect with maximum heat exposure. The research provides actionable insights for climate-sensitive urban planning, emphasizing the urgent need for targeted, nature-based solutions and infrastructure investment to mitigate UHI effects and enhance the adaptive capacity of the most vulnerable urban communities.
subject: Research Article
  topic: section
subject: Urban Heat Islands, Megacities, Climate Vulnerability, Heat Exposure Inequality, Urban Resilience
  topic: keywords
creator: Priyanka Ashfin
rights: Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2023-12-20
publication date: 2023-12-20
starting page: 01
ending page: 10
doi: 10.32996/bjmss.2023.2.2.1

Optimizing Vaccine Distribution Networks in Heterogeneous Populations Using Geospatial Data and Demographic Risk Models
type: item
description: Effective and equitable vaccine distribution is a complex logistical challenge, especially during pandemics. Traditional, one-size-fits-all strategies often fail to address the heterogeneity within populations, leading to inadequate service for high-risk and vulnerable subgroups. This study introduces a novel, integrated approach to optimize vaccine distribution networks by leveraging multi-source geospatial data and advanced demographic risk models. Methods: The proposed framework utilizes Geographic Information Systems (GIS), spatial statistics, and operational research to overcome the limitations of standard models. It dynamically integrates key metrics—including population density, vulnerability, healthcare access, and logistical constraints—to effectively prioritize resource allocation. This integration allows for a nuanced, data-driven approach that moves beyond simplistic population-based strategies. Results: The optimized distribution strategy allocates resources based not only on density but also on vulnerability and access metrics, ensuring that the most at-risk communities are prioritized. This refined approach enables the effective deployment of mobile vaccination centers and strategic placement of fixed sites. By considering epidemiological risk and socio-economic determinants, this framework significantly enhances accessibility and equity, preventing the exacerbation of existing health disparities. Conclusion: The integration of geospatial and demographic risk modeling provides a more nuanced and equitable framework for vaccine resource allocation, thereby enhancing public health outcomes during mass vaccination efforts. Further refinement through microplanning is essential, particularly in resource-limited settings, to precisely identify and reach all target populations.
subject: Research Article
  topic: section
subject: Vaccine Distribution Optimization, Geospatial Health Analytics, Health Equity, Facility Location-Allocation Modeling, Demographic Risk Stratification
  topic: keywords
creator: Oritsemeyiwa Gabriel Orugboh
creator: Ofeoritse Gift Omabuwa
creator: Omotoyosi Simisola Taiwo
rights: Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2023-06-20
publication date: 2023-06-20
starting page: 11
ending page: 20
doi: 10.32996/bjmss.2023.2.1.2

Telemedicine Adoption and Health Equity: Evaluating Access, Quality, and Patient Outcomes in Low-Resource Settings
type: item
description: Telemedicine has emerged as a critical tool for expanding healthcare access, particularly in low-resource settings where shortages of medical professionals, weak infrastructure, and geographic barriers limit the availability of quality care. The COVID-19 pandemic accelerated telemedicine adoption worldwide, highlighting its potential to reduce service gaps and strengthen health system resilience. However, disparities in digital access, literacy, and affordability continue to influence who benefits from these technologies. This study evaluates the relationship between telemedicine adoption, health equity, and patient outcomes in resource-constrained environments. Drawing on recent empirical research, policy reports, and global health case studies, the paper examines how telemedicine impacts access to care, diagnostic accuracy, continuity of treatment, and patient satisfaction. Findings suggest that telemedicine can significantly improve health outcomes by enabling remote consultations, early disease detection, and efficient referral pathways. Yet, persistent inequities—including limited broadband connectivity, device scarcity, low digital literacy, and gender- or income-based barriers—undermine the equitable distribution of these benefits. The study concludes that telemedicine can advance health equity only when supported by inclusive digital infrastructure, capacity-building initiatives, culturally appropriate design, and strong regulatory frameworks. These insights offer evidence-based guidance for policymakers, healthcare providers, and global health organisations working to ensure that digital health innovations improve outcomes for the most underserved populations.
subject: Research Article
  topic: section
subject: Non-communicable diseases, South Asia, Health systems, Prevention strategies, Public health policy
  topic: keywords
creator: Md Nazmul Hoque
rights: Copyright (c) 2023 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2023-06-20
publication date: 2023-06-20
starting page: 01
ending page: 10
doi: 10.32996/bjmss.2023.2.1.1

Consumer Trust in E-Commerce: The Role of Personalisation, Security, and Brand Authenticity
type: item
description: Consumer trust has become a critical determinant of success in the rapidly expanding e-commerce landscape. As online marketplaces grow increasingly competitive, businesses must prioritise trust-building strategies to attract, engage, and retain customers. This study examines how three key factors—personalisation, security, and brand authenticity—shape consumer trust in digital commerce environments. Personalisation enhances user experience by delivering tailored recommendations, adaptive interfaces, and relevant product offerings, thereby strengthening emotional connection and perceived value. Security mechanisms, including data protection, secure payment systems, and transparent privacy policies, significantly influence consumers’ willingness to transact online and reduce perceived risk. Brand authenticity, grounded in transparency, consistent communication, and ethical business conduct, fosters credibility and long-term loyalty. Through a synthesis of current literature and emerging industry practices, this paper explores the interplay between these dimensions and their collective impact on consumer trust formation. The study argues that e-commerce platforms must integrate personalised experiences with robust security frameworks and genuine brand identity to cultivate strong and sustainable consumer trust. These insights offer valuable implications for digital marketers, platform designers, and policymakers seeking to strengthen trust and engagement within the online marketplace.
subject: Research Article
  topic: section
subject: Predictive algorithms, algorithmic bias, digital surveillance, social inequality, automated governance
  topic: keywords
creator: Md Naim Mukabbir
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2024-12-20
publication date: 2024-12-20
starting page: 18
ending page: 26
doi: 10.32996/bjmss.2024.3.2.3

Digital Pedagogy in the Post-Pandemic Era: Opportunities and Inequalities in Higher Education
type: item
description: The COVID-19 pandemic accelerated the global shift toward digital pedagogy, transforming teaching and learning practices across higher education. While this transition expanded opportunities for flexible learning, technological innovation, and new forms of student engagement, it also exposed and deepened structural inequalities within and between institutions. This paper examines the post-pandemic evolution of digital pedagogy, analysing both its potential and its challenges. Opportunities include the integration of adaptive learning technologies, wider access to open educational resources, enhanced collaboration through digital platforms, and the growth of hybrid and personalised learning models. However, significant inequalities persist due to disparities in digital access, technological infrastructure, digital literacy, and institutional readiness—particularly affecting students from low-income backgrounds, rural communities, and resource-constrained universities. The study also explores how faculty workload, assessment integrity, and pedagogical quality have been reshaped in the digital era. It argues that achieving equitable and effective digital pedagogy requires sustained investment in infrastructure, inclusive technology design, targeted capacity-building, and policies aimed at reducing the digital divide. Ultimately, the paper highlights that while digital pedagogy holds transformative potential for higher education, its long-term success depends on addressing inequalities and ensuring that technological progress benefits all learners.
subject: Research Article
  topic: section
subject: Digital Pedagogy; Post-Pandemic Era; Opportunities; Inequalities; Higher Education
  topic: keywords
creator: Sarmi Islam
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2024-12-20
publication date: 2024-12-20
starting page: 09
ending page: 17
doi: 10.32996/bjmss.2024.3.2.2

Urban Heat Islands and Climate Vulnerability: Assessing Risks in Rapidly Growing Megacities
type: item
description: Urban Heat Islands (UHIs) have emerged as a critical environmental challenge in rapidly growing megacities, driven by uncontrolled urbanisation, loss of green cover, high-density built environments, and increased anthropogenic heat emissions. As global temperatures rise, UHIs intensify local warming, amplifying climate vulnerability for millions of urban residents. This study examines the spatial patterns, drivers, and consequences of UHI formation in megacities, with particular attention to human health risks, energy demand pressures, and socio-ecological inequalities. Findings from recent urban climate research show that low-income and densely populated neighbourhoods experience disproportionately higher heat exposure, exacerbating heat-related illnesses and straining public infrastructure. The paper also analyses how climate change interacts with UHI effects, creating compound risks such as extreme heatwaves, reduced air quality, and heightened mortality. Finally, the study outlines evidence-based mitigation pathways—including urban greening, reflective materials, sustainable building design, and improved climate governance—to enhance resilience in rapidly urbanising regions. The research argues that addressing UHIs is essential for ensuring sustainable urban development, protecting vulnerable populations, and strengthening adaptive capacity in the face of accelerating climate change.
subject: Research Article
  topic: section
subject: Urban Heat Islands, Megacities, Climate Vulnerability, Heat Exposure Inequality, Urban Resilience
  topic: keywords
creator: Priyanka Ashfin
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0
date: 2024-12-20
publication date: 2024-12-20
starting page: 01
ending page: 08
doi: 10.32996/bjmss.2024.3.2.1

From Automation to Augmentation: How Generative AI Is Reshaping the Global Workforce
type: item
description: Generative artificial intelligence (AI) is transforming the global workforce by shifting the focus from traditional automation toward human–AI augmentation. While earlier waves of automation primarily replaced routine, rule-based tasks, generative AI now enhances creativity, decision-making, and complex problem-solving across industries. This shift has major implications for productivity, workforce skill requirements, and organisational structures. The technology enables faster content generation, improved data analysis, personalised customer interactions, and streamlined operational workflows. At the same time, it introduces new challenges related to job displacement risks, ethical concerns, skill mismatches, and the need for responsible governance frameworks. This paper examines how generative AI is reshaping labour markets worldwide by augmenting human capabilities rather than merely substituting labour. It analyses industry-level transformations, emerging patterns of human–AI collaboration, and the policy and training interventions required to ensure an inclusive and future-ready workforce. Ultimately, the study argues that generative AI holds the potential to unlock significant economic and social value when deployed responsibly and aligned with long-term human development goals.
subject: Research Article
  topic: section
subject: Generative AI, Workforce Transformation, Human–AI Collaboration, Skill Augmentation, Ethical Governance
  topic: keywords
creator: Ura Ashfin
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0
date: 2024-06-05
publication date: 2024-06-05
starting page: 08
ending page: 15
doi: 10.32996/bjmss.2024.3.1.2

The Rising Burden of Non-Communicable Diseases in South Asia: Challenges and Policy Pathways for Prevention
type: item
description: Non-communicable diseases (NCDs) have emerged as one of the most significant public health challenges in South Asia, driven by rapid urbanisation, lifestyle transitions, demographic changes, and persistent health system constraints. Countries such as Bangladesh, India, Pakistan, Sri Lanka, and Nepal are witnessing rising rates of cardiovascular diseases, diabetes, chronic respiratory illnesses, and cancers, contributing to a growing share of premature morbidity and mortality. Despite progress in primary healthcare and health promotion, structural barriers—including limited preventive services, weak surveillance systems, inequitable access to care, and socioeconomic disparities—continue to impede effective NCD management. This paper examines the key determinants behind the increasing burden of NCDs in South Asia and analyses the policy gaps that hinder regional progress. It further outlines evidence-based pathways for prevention, including strengthening primary care, enhancing community-level awareness, integrating digital health solutions, promoting multisectoral action on risk factors, and improving financial protection mechanisms. The study argues that a comprehensive, coordinated, and equity-focused policy response is essential to mitigate the rising NCD burden and ensure healthier futures for South Asian populations.
subject: Research Article
  topic: section
subject: Non-communicable diseases, South Asia, Health systems, Prevention strategies, Public health policy
  topic: keywords
creator: Md Nazmul Hoque
rights: Copyright (c) 2024 https://creativecommons.org/licenses/by/4.0/
date: 2024-06-03
publication date: 2024-06-03
starting page: 01
ending page: 07
doi: 10.32996/bjmss.2024.3.1.1

Artificial Intelligence as a Social Actor: Reconfiguring Power, Identity, and Agency in Contemporary Societies
type: item
description: The rapid integration of Artificial Intelligence (AI) into everyday social systems has reshaped long-standing sociological understandings of power, identity, and human agency. This paper explores AI not merely as a technological tool but as an emerging social actor capable of influencing behaviours, shaping decision-making processes, and redefining institutional practices. Drawing on theories of symbolic interactionism, actor–network theory, and critical sociology, the study examines how AI systems mediate social interactions, produce new forms of algorithmic authority, and contribute to shifting power relations between individuals, organisations, and the state. The analysis highlights how AI-driven classifications, predictions, and automated decisions reshape identities—through profiling, personalisation, and digital surveillance—while also raising concerns over autonomy, inequality, and ethical accountability. By conceptualising AI as a socially embedded actor, the paper argues that AI technologies have begun to co-produce social realities, redistribute control, and challenge the boundaries between human and machine agency. This reconfiguration demands renewed sociological attention toward digital governance, transparency, and the societal impacts of algorithmic systems in increasingly automated environments.
subject: Research Article
  topic: section
subject: Artificial Intelligence, social agency, algorithmic authority, digital surveillance, power relations
  topic: keywords
creator: Md Nazmul Hoque
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-11-27
publication date: 2025-11-27
starting page: 49
ending page: 57
doi: 10.32996/bjmss.2025.4.1.5

Predictive Algorithms and Social Inequality: A Sociological Analysis of Bias, Governance, and Digital Surveillance
type: item
description: The rapid expansion of predictive algorithms across social, economic, and governmental systems has intensified concerns about the reproduction of inequality and the emergence of new forms of algorithmic governance. This paper examines how predictive technologies—ranging from risk-assessment tools and automated hiring systems to credit-scoring platforms and predictive policing—systematically shape opportunities, access, and social outcomes. Drawing on insights from sociology, critical data studies, and surveillance theory, the study analyses the mechanisms through which algorithmic systems encode historical biases, amplify structural disadvantages, and normalise surveillance as a mode of social control. The paper argues that predictive algorithms operate within unequal data infrastructures that disproportionately disadvantage marginalised groups, reinforcing patterns of racialised, gendered, and class-based exclusion. Moreover, the opacity of algorithmic decision-making and the rise of automated governance shift power away from public accountability and towards computational forms of authority controlled by states and corporations. By situating predictive technologies within broader socio-political contexts, this paper highlights the urgent need for transparent modelling practices, anti-bias regulation, and equitable data governance frameworks. The findings contribute to ongoing debates about digital injustice and provide a sociological foundation for understanding how algorithmic systems reshape power, surveillance, and inequality in the digital age.
subject: Research Article
  topic: section
subject: Predictive algorithms, algorithmic bias, digital surveillance, social inequality, automated governance
  topic: keywords
creator: Md Naim Mukabbir
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-11-27
publication date: 2025-11-27
starting page: 40
ending page: 48
doi: 10.32996/bjmss.2025.4.1.4

How Oracle Cloud Helps Enterprises Achieve True Cloud Sovereignty
type: item
description: In an era of mounting regulatory burdens, geopolitical uncertainty, and escalating cyber-threats, enterprises must reconcile the agility and innovation of cloud computing with stringent demands for data sovereignty, operational control, and regional compliance. This paper examines how Oracle Cloud Infrastructure (OCI) is architected to support enterprises in achieving true cloud sovereignty. First, it defines the core tenets of digital sovereignty — data residency, privacy & access control, security & resiliency, and legal/operational jurisdiction — and outlines the rising global pressure on organisations to conform to these requirements. Drawing on Oracle’s sovereign-cloud offerings (including dedicated regions, isolated/air-gapped environments and regionally-compliant zones), the paper explains how OCI enables enterprises to maintain full control over where data resides, who can access it, and how it is processed — while still benefiting from the scalability, flexibility and efficiency of cloud services. Key capabilities such as autonomous region deployments, customer-managed encryption keys, strict operator access controls and full service parity across sovereign and commercial clouds are explored. The analysis highlights how enterprises can leverage these capabilities to ensure legal compliance, strengthen trustworthiness with stakeholders, support AI and analytics workloads without compromising sovereignty, and embed resilience against supply-chain or geopolitical disruption. The paper also discusses the challenges associated with sovereign clouds — such as service feature parity, vendor lock-in risks, and cost/complexity trade-offs — and offers strategic guidance for enterprise adoption. In conclusion, by aligning cloud architecture with sovereignty-centric design, enterprises can transform regulatory constraint into strategic advantage: securing data, innovating dynamically, and operating with confidence in a world where sovereignty matters.
subject: Research Article
  topic: section
subject: Oracle Cloud; Enterprises; True Cloud Sovereignty
  topic: keywords
creator: Sarmi Islam
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-11-27
publication date: 2025-11-27
starting page: 27
ending page: 39
doi: 10.32996/bjmss.2025.4.1.3

Designing High Availability Architectures on Oracle Cloud Infrastructure (OCI)
type: item
description: Designing high availability (HA) architectures on Oracle Cloud Infrastructure (OCI) is fundamental to ensuring continuous operations, fault tolerance, and minimal service disruption for mission-critical enterprise workloads. OCI provides a comprehensive set of tools and architectural patterns—such as multi-availability domains (ADs), fault domains (FDs), load balancers, autonomous services, and disaster recovery regions—to build resilient and self-healing systems. This study explores how OCI’s distributed design, coupled with its networking and storage redundancy features, enables organizations to achieve five-nines availability while optimizing cost and performance. The paper examines architectural blueprints for key workloads, including web applications, databases, and containerized environments, highlighting the use of features like Oracle Data Guard, Traffic Management Steering Policies, and the Service Gateway for continuous access and failover. Furthermore, it evaluates design considerations such as synchronous replication, automated backup policies, and monitoring through Oracle Cloud Observability and Management services. By adopting these HA strategies, enterprises can align business continuity objectives with OCI’s native cloud-native capabilities, achieving scalable, secure, and resilient cloud architectures that withstand infrastructure, network, and application-level failures.
subject: Research Article
  topic: section
subject: High availability, OCI architecture, fault tolerance, disaster recovery, Oracle Data Guard
  topic: keywords
creator: Priyanka Ashfin
rights: Copyright (c) 2025 https://creativecommons.org/licenses/by/4.0/ https://creativecommons.org/licenses/by/4.0/
date: 2025-11-27
publication date: 2025-11-27
starting page: 15
ending page: 26
doi: 10.32996/bjmss.2025.4.1.2

Why Multicloud Is the New Normal
type: item
description: Multicloud has rapidly shifted from an emerging option to the dominant operating model for modern enterprises. Recent surveys indicate that well over 85–90% of large organizations now use more than one cloud provider, and many run meaningful workloads across three or more platforms. Integrate.io+1 This abstract argues that multicloud is becoming the new normal because it aligns technical, economic, and regulatory realities better than single-cloud or purely on-premises strategies. Technically, multicloud lets organizations match each workload to the most suitable platform, combining best-of-breed services in analytics, AI, storage, and edge while improving performance and resilience.Oracle+1 Economically, distributing workloads across vendors strengthens negotiating power, mitigates the risk of sudden price or policy changes, and supports more granular cost optimization.Netguru+1 From a risk and compliance perspective, hosting data and applications in multiple jurisdictions and architectures enhances business continuity and helps meet data-sovereignty and sectoral regulatory requirements.Qlik+1 However, the abstract also highlights that this “new normal” introduces significant complexity in governance, security, skills, and integration, demanding unified observability, strong architectural standards, and automation-driven operations to unlock its full value.
subject: Research Article
  topic: section
subject: Multicloud, workload optimization, data sovereignty, cost efficiency, governance complexity
  topic: keywords
creator: Ura Ashfin
rights: Copyright (c) 2025 British Journal of Multidisciplinary Studies https://creativecommons.org/licenses/by/4.0/
date: 2025-11-27
publication date: 2025-11-27
starting page: 01
ending page: 14
doi: 10.32996/bjmss.2025.4.1.1