With the rise of the digital transformation era, healthcare organizations are getting more inclined toward using Business Intelligence (BI) tools as a means of improving clinical outcomes and operational efficiency. This article explores the diverse nature of BI in the healthcare system in the optimization of data-driven decisions. Through secondary data analysis (mixed-method approach with the empirical case studies), the research focuses on the ways of implementing the BI tools (dashboards, predictive analytics platforms, and real-time reporting systems) to enhance clinical diagnostics, workflow efficiency, and operational cost-reduction. The study notes the application of BI to Electronic Medical Records (EMRs), hospital performance dashboards, and administrative systems to deliver actionable insights by analysing huge, disparate data sources. Results of recent large-scale studies show that BI implementation may help shorten patient wait time by as much as 35 percent, reduce hospital readmission rates by 20 percent and help optimize staff use by 25 percent, Friends, leading to enhanced patient satisfaction and reduced costs. Besides, the comparative examination illustrates that, owing to the resourcefulness, the adoption of BI in the private sector hospitals is nimbler than that of the governmental counterparts. Also, the essential obstacles recognized in the study include data silos, change resistance, and interoperability. The paper is able to contribute to the developing literature because it is able to synthesize the real-world applications and evaluate their practical effects on care delivery. The results point towards the importance of strategic BI investments and strong data governance models. Healthcare organizations can take a step forward to transparent, informed, and value-based care by fixing these problems. The study does not only address a major gap but also provides a valuable guide on how BI can be integrated in the future in healthcare environments worldwide.

Multinational companies (MNEs) are challenged increasingly by the requirement to report under multiple accounting frameworks like US GAAP, IFRS, and local GAAPs. ERP systems based on traditional architecture are incapable of providing harmonized and compliant reporting under this multiplicity of environments. Oracle Accounting Hub Cloud Service (AHCS) is a traditional, centralized accounting solution that consolidates disparate source systems to process parallel accounting treatments under a range of GAAPs. The paper discusses the architecture capabilities, compliance attributes, and strategic benefits of Oracle AHCS through in-depth analysis and a case study of its real-world implementation at A Life Sciences company. The findings suggest that AHCS improves auditability, minimizes close cycles, ensures precision, and supports geographies with scalable accounting efficiently.

AI is now playing a key role in healthcare by giving rise to new possibilities in diagnostics, planning care, using resources wisely, and developing the right strategy for organizations. Here, the focus is on learning how healthcare organizations can make better decisions in business by using AI technologies. Both secondary research and insights from digitalized hospitals are used to study this topic. General data was gathered from existing health performance dashboards, yet calculations from machine learning were also used, along with reviews of how ready the organization is and interviews with stakeholders for qualitative insights. Researchers have found out that the use of AI-based tools in healthcare organizations leads to a 45% drop in errors during diagnosis and a 30% decrease in expenses related to management. It was also important for AI tools to match the business’s IT infrastructure to help the company become agile in its strategy. Still, there are challenges such as data not sharing well, biased algorithms, and lack of acceptance of technological updates that keep most people from adopting data science. The study provides insight into the current field of healthcare by offering a unified framework for healthcare administration, artificial intelligence, and business information systems. What makes this research stand out is that it looks at AI’s uses in medicine and in the process of making high-level decisions. At the end, the paper offers practical steps that healthcare leaders should consider to shapes long-term strategies by using AI.

The article analyzes the application of emotional marketing and storytelling in the development and promotion of bridal collection brands. Emotional marketing generates narratives that awaken profound feelings and value-based associations, while storytelling constructs the collection’s image as a “character” with its own history and cultural context. The relevance of this topic is determined by widespread demand for a personalized experience and a deep affective bond with the brand in the selection of wedding items, where consumers prioritize symbolic and emotional motives over purely rational product attributes. The aim of the study is to examine the theoretical and methodological foundations, as well as practical aspects, of employing emotional marketing and storytelling tools to optimize branding strategies intended to enhance the brand equity of a bridal collection. To achieve this, descriptive and content analyses of academic publications and market data from the past five years were conducted, which made it possible to identify the main strategic directions and macrotrends in the use of emotional technologies in wedding collection marketing. The findings are of practical interest to marketers, brand managers, designers, and consumer behavior researchers, demonstrating that the integration of authentic, emotionally rich narratives into a brand’s communication architecture acts as a catalyst for a deep emotional connection with the audience, increases the perceived value of the offering, serves as a reliable predictor of purchase decisions, and promotes organic content dissemination and sustainable growth of market share.

In this study a comprehensive analysis of the efficiency of implementing LiDAR technology (Light Detection and Ranging) in the formation of high-precision digital terrain models (DTMs) in the course of large-scale topogeodetic surveys is carried out. The aim of the research is to evaluate LiDAR accuracy indicators, economic feasibility and operational performance relative to classical photogrammetry, taking into account the use of unmanned aerial vehicles (UAVs). The methodological basis of the research includes a review of publications, synthesis of data from these works and statistical data analysis. The results obtained indicate that LiDAR provides an advantage in digitizing terrain under dense vegetation cover. An algorithm for selecting the optimal method is proposed, based on multi-criteria analysis which includes vegetation density, accuracy requirements and project budget constraints. The key findings of the study emphasize the superiority of LiDAR in complex natural-landscape conditions and the economic viability of photogrammetry in areas with open terrain, which justifies the feasibility of a hybrid approach to optimize costs and improve the quality of the output DTMs. The study will be useful for surveying engineers, GIS specialists, managers of construction and infrastructure projects, as well as researchers in the field of Earth remote sensing.

Forcados-Yokri field is situated in Burutu area of Delta State. Its a large oil and gas province holding large volume of recoverable hydrocarbon. A Geological redevelopment was done to harness the abundant gas contained in it. There is urgent need for Nigeria to shift to cleaner source of alternative energy and reduce its carbon footprint, thus, the block was re-evaluated and re-developed for this gas deposit. The field was thus initiated to supplement gas production for domestic reserve and enhance the industrialization of the region and the country. The field has an expected STOIIP and GIIP (AG + NAG) of 2878 MMstb oil and 2298.7 Bscf of gas respectively. Cluster Jackets, 18" x 5.5km Oil Pipeline  12" x 6.4km Gas Pipeline, 33KV Power Cable Back-up, 8" Gas lift line (North Bank Gas Plant-Yokri Flowstation), new cluster jackets, 33kV Cable from North Bank Manifold, 700V Power Control Cable Ring were connected to the main Pipeline Phase 1. More importantly, 6" South Bank to Forcados Terminal fuel gas back-up Line, 8 km and 6“ flow line were also connected to slug catcher at North Bank Gas Processing Facilities with the existing Associated Gas facilities at the CPF. Findings revealed feasible environmental space for gas production with phytoplankton distribution of Bacillariophyceae 52%, Cyanophyceae 33%, Euglenophyceae 7%, Dinophycea 5%, Chlorophyceae 3% with the zooplankton belonged to six (6) taxa; Copepoda, Hydrozoa, Mollusc larvae, Decapod larvae, Rotifera, and Chaetognatha. The study concluded the feasibility and viability of producing the hydrocarbon content of about 291MMstb of oil and 94 bscf of gas in the block area under the prevailing environmental condition.

The article discusses the appearance of voltage deviations in the power transmission line as a result of connecting more and more electric consumers with different resistance to the power supply line and the assessment of its negative impact on the efficiency and reliability of power transformers during long-term operation. In the LD DIDACTIC laboratory complex, the connection schemes of the power transformer with a total capacity of 360 VA were changed and the voltage deviation from the nominal value is brought to the supply line. The values of the voltage deviation generated in the power transformer were determined when loads with different resistance is connected to the secondary output terminals of the power transformer. Based on the obtained results, it is possible to evaluate the performance of the power transformer.

Cloud computing can result in a reduction of carbon emissions by up to 87% and energy cost savings of over 80% compared to traditional on-premise data centers, and is a fundamental tool for realizing ESG goals. The present paper examines the environmental, social, and governance (ESG) impacts of cloud hosting versus legacy infrastructure, with specific reference to enterprise resource planning (ERP) systems. Using sustainability metrics and case studies relating to Netflix, Capital One, Spotify, and Betabrand, the paper demonstrates that cloud adoption represents not only a technical upgrade from existing legacy infrastructure but also a realignment of strategy for future-proof digital infrastructure. The study revealed that cloud infrastructure allows organizations to benefit from; IT agility, compliance, equitable access, and responsible digital transformation of critical business processes. With the increasing strictness of global ESG regulations, cloud computing not only provides a competitive advantage but also lays the moral foundation for an organization’s future-proof digital infrastructure strategy.

Digital transformation of hospitals is transforming the provision of healthcare services through the incorporation of sophisticated information technologies into clinical, operational, and administrative hospital systems. However, even with such heavy investments in the digital health infrastructure, one everything seems to be persistently missing: the ability to accurately assess the return on investment (ROI) of such technologies both in financial performance and patient care outcomes. The research question of this paper is the ROI of IT investments in hospitals; the multidimensionality of the impact of digital systems (Electronic Health Records, Clinical Decision Support Systems, telemedicine platforms, and data analytics dashboards) will be considered. With the quantitative research design, the research study will examine the data provided on the financial reports of the hospital, operational and clinical outcome indicator data to quantify the cost-effectiveness and value-creating measures. The main findings indicate that hospitals at the stage of a developed digital ecosystem are characterized by a significant increase in budget efficiency, a decrease in errors, an increased productivity of the staff, and an increase in the recovery rates of patients. Another revelation of the study is that ROI is not just about financial benefit but also includes benefits in workflow streamlining, decision correctness, and long-term viability. This study adds to this body of evidence by synthesizing, in financial, clinical, and operational spheres, an overall structure of IT investment assessment in health systems. This research is also novel because of its data science approach, cross-functional analysis, and prescriptive recommendations that can be used by hospital managers and health policymakers. The results highlight a strong necessity of systematic ROI assessment plans that will direct prospective digital spending plans and align them with institutional objectives. The paper is an essential source of reference in accelerating evidence-based IT adoption in healthcare and achieving optimum value on digital transformation initiatives.

The paper analyses core data-management strategies that ensure a consistent, scalable, and cost-efficient transition from on-premises or monolithic relational databases to Amazon Aurora Serverless. Drawing on recent peer-reviewed research and industry reports, the study first frames serverless Aurora within a microservice-centric architecture, emphasising the “database-per-service” pattern, CAP-theorem trade-offs, and the complementary roles of transactional stores, data lakes, and data warehouses. The second section evaluates mechanisms for maintaining data integrity during and after migration, contrasting ACID guarantees in Aurora with BASE-oriented eventual consistency at the system boundary, and detailing patterns such as sagas and event sourcing for cross-service coordination. The third part (retained in full) offers a practice-oriented synthesis of automation techniques: AWS Database Migration Service for zero-downtime change-data-capture, AWS Schema Conversion Tool for heterogeneous schema conversion, and Infrastructure-as-Code pipelines for repeatable cluster provisioning and continuous delivery. Empirical evidence from large-scale migrations—including multi-billion-row financial and media platforms—is used to quantify benefits (e.g., up to 40 % cost reduction and sub-minute fail-over times) and to highlight common pitfalls. The paper concludes with a set of actionable guidelines that align architectural decisions, consistency requirements, and automation practices, demonstrating that a properly orchestrated move to Aurora Serverless not only preserves, but often enhances enterprise data reliability and agility.

This article presents a comprehensive, theoretically grounded synthesis and original conceptual framework for designing fault-tolerant, model-based test infrastructures applicable to large-scale software systems—particularly service compositions, web services, cloud and edge resource management, and GPU manufacturing testing ecosystems. It integrates formal modeling techniques, graph-transformation semantics, model-based verification and test generation, and modern fault-tolerant resource provisioning strategies. The theoretical backbone draws on operational semantics for behavioral diagrams, graph transformation for reconfiguration and verification, model checking for test generation, and recent research on fault tolerance in cloud and edge contexts. The contribution is a unified, extensible methodology and architecture that couples dynamic meta-modeling and graph-based semantics (for formal, tool-supportable behavioral specifications) with model-driven test generation and adaptive fault-tolerant resource allocation mechanisms for runtime and pre-deployment validation. The framework addresses core challenges: representing compositional behavior of service orchestrations, generating tractable yet effective test sets from rich behavioral models, ensuring conformance and reliability under failure modes, and maintaining scalable resource allocation across cloud-edge infrastructures. The article details modelling conventions, transformation rules, verification and test case extraction processes, and fault-tolerance policies that guide resource management and test scheduling. It further articulates practical design principles for test infrastructures in production-scale contexts (for example, GPU manufacturing test farms and large cloud-based service compositions) and discusses trade-offs among test thoroughness, cost, and fault coverage. Limitations are discussed and a roadmap for empirical validation and toolchain integration is laid out. The work aims to serve both as an academic synthesis bridging multiple literatures and as a practical blueprint for engineering resilient test infrastructures for modern distributed systems.

News organizations have grown increasingly reliant on large file transfer systems for time-sensitive media operations, regularly managing multi-gigabyte video content through enterprise platforms like MediaShuttle, Aspera, and Microsoft FTP Server while working against tight editorial deadlines. This digital shift in journalism workflows appears to have left media infrastructures vulnerable to sophisticated cyber attacks. Threat actors seem particularly drawn to exploiting file transfer weaknesses as a pathway to sensitive content and newsroom disruption, which became starkly evident during the 2023 MOVEit breach that impacted the BBC. Yet current threat modeling frameworks, built primarily for general enterprise settings, may not adequately capture the distinct operational pressures and security needs that define newsroom file transfer environments. This study is the first to apply the STRIDE threat modeling framework to journalism file transfer systems. The new framework combines STRIDE with Zero Trust principles to address security risks in editorial workflows. Through validation across case studies involving three varied news organizations, the framework demonstrated what appears to be a 40% enhancement in threat identification capabilities and uncovered 23 previously overlooked vulnerabilities. This research offers systematic methods for securing file transfer operations without compromising editorial workflow efficiency. It provides theoretical groundwork for journalism cybersecurity research while delivering practical implementation guidance that media organizations can actually use.

The development of ceramic pigments with a willemite structure through the utilization of industrial by-products, such as microsilica, represents a promising and sustainable research direction. In this study, pigments in the ZnO–CoO–SiO2 system were synthesized using microsilica as a silica source. The influence of raw material composition and firing conditions on phase formation, crystal structure, and color characteristics of the pigments was investigated. X-ray diffraction (XRD) analysis confirmed the formation of willemite-based solid solutions. The colorimetric properties were evaluated in the CIE Lab* system, demonstrating that the obtained pigments exhibit stable blue and violet hues with high thermal and chemical resistance. The results highlight the potential of microsilica recycling for the production of cost-effective, environmentally friendly ceramic pigments suitable for glaze and ceramic applications.

Energy efficiency is becoming an increasingly important consideration in the design of satellite communication systems. With the rapid expansion of satellite constellations and the ever-growing demand for high-performance communication services, the need for energy-efficient satellite systems has never been greater. This review aims to analyze the key components and strategies for energy-efficient design in satellite communication systems, considering various technological innovations and approaches in the field. The paper examines the role of power consumption in different segments of satellite systems, including ground stations, on-board payloads, communication links, and satellite architectures. Furthermore, we explore optimization techniques, such as adaptive power control, power-efficient coding, and the integration of renewable energy sources, to reduce energy consumption. We also discuss the environmental and economic impacts of energy efficiency improvements and propose recommendations for future developments in this area.