Data Analytics Research Articles

Analysing the Customer Retention Strategies of Subscribers of "Over-The-Top" (OTT) Media Streaming Services: Capturing the Insights of Urban Consumers using Data Analytics

Analysing the Customer Retention Strategies of Subscribers of "Over-The-Top" (OTT) Media Streaming Services: Capturing the Insights of Urban Consumers using Data Analytics

Big data analytics usage in the banking industry in Tanzania: does perceived risk play a moderating role on the technological factors

PurposeThe main purpose of this paper is to examine the adoption of big data analytics (BDA) in the Tanzania banking industry by investigating the influence of technological, environmental and organizational (TOE) factors while exploring the moderating role of perceived risk (PR).Design/methodology/approachThe study employed a qualitative research design, and the research instrument was developed using per-defined measurement items adopted from prior studies; the items were slightly adjusted to fit the current context. The questionnaires were distributed to top and middle managers in selected banks in Tanzania using the snowball sampling technique. Out of 360 received responses, 302 were considered complete and valid for data analysis. The study employed partial least squares structural equation modeling (PLS-SEM) to examine the developed conceptual framework.FindingsTop management support and financial resources emerged as influential organizational factors, as did competition intensity for the environmental factors. Notably, bank size and perceived trends showed no significant impacts on BDA adoption. The study's novelty lies in revealing PR as a moderating factor, weakening the link between technological readiness, perceived usefulness and the intent to adopt BDA.Originality/valueThis study extends literature by extending the TOE model, through examining the moderating roles of PR on technological factors. Furthermore, the study provides useful managerial support for the adoption of BDA in banking in emerging economies.

Technological innovations and optimized work methods in subsea maintenance and production

Subsea maintenance and production represent critical aspects of offshore operations, vital for sustaining energy production and ensuring operational efficiency. However, these endeavors face numerous challenges, including the complexities of deepwater environments, harsh weather conditions, and the high costs associated with traditional maintenance methods. To address these challenges, this paper explores the integration of technological innovations and optimized work methods in subsea operations. Technological innovations play a pivotal role in revolutionizing subsea maintenance and production. Remote monitoring and control systems enable real-time data collection and decision-making, enhancing operational visibility and efficiency. Autonomous underwater vehicles (AUVs) offer the capability to conduct inspections and repairs in remote and hazardous environments, reducing human intervention and associated risks. Robotics and automation further streamline maintenance tasks, improving accuracy and reducing downtime. Advanced materials and coatings enhance equipment durability and corrosion resistance, prolonging asset lifecycles and reducing maintenance requirements. In parallel, optimized work methods offer strategic approaches to enhance subsea operations' effectiveness. Predictive maintenance strategies leverage data analytics and machine learning to anticipate equipment failures, enabling proactive interventions and minimizing downtime. Condition-based monitoring facilitates real-time assessment of asset health, enabling timely maintenance interventions and cost savings. Integrated asset management systems provide holistic insights into asset performance and facilitate informed decision-making. Lean operations and continuous improvement methodologies further optimize workflows, driving operational excellence and cost efficiency. Through case studies and industry examples, this paper highlights the successful implementation of technological innovations and optimized work methods in subsea maintenance and production. Furthermore, it explores future trends, regulatory considerations, and the importance of industry collaborations in shaping the future of subsea operations. Ultimately, the integration of these approaches offers a pathway towards enhanced operational efficiency, reduced costs, and sustainable subsea operations. Keywords: Technological Innovations, Optimized Work Methods, Subsea Maintenance and Production.

StudyNotion - An Edtech Website

In an era defined by rapid technological advancement, education stands as a crucial arena ripe for transformation. Our Edtech website emerges as a beacon of innovation, aiming to revolutionize traditional learning paradigms through the seamless integration of cutting-edge technology. With a multifaceted approach, our platform offers a comprehensive suite of tools and resources tailored to meet the diverse needs of students, educators, and institutions alike. At the heart of our platform lies a commitment to accessibility and inclusivity, ensuring that learning opportunities transcend geographical boundaries and socioeconomic barriers. Through interactive modules, engaging content, and personalized learning pathways, we empower learners to cultivate their intellectual curiosity and unlock their full potential. For educators, our platform serves as a dynamic hub for professional development, fostering collaboration, and knowledge sharing within a vibrant community of practice. From virtual classrooms to collaborative project management tools, we provide the scaffolding necessary to facilitate effective teaching in the digital age.Furthermore, our platform harnesses the power of data analytics and artificial intelligence to deliver actionable insights and personalized recommendations, facilitating data-driven decision-making and enhancing learning outcomes. In essence, our Edtech website represents more than just a digital learning platform; it embodies a vision for the future of education—one where technology serves as a catalyst for empowerment, innovation, and lifelong learning. Join us on this transformative journey as we redefine the possibilities of education in the 21st century and beyond. This abstract succinctly captures the essence of the Edtech website, highlighting its goals, features, and the transformative potential it holds for education.The abstract for the Edtech Website project encapsulates the endeavor to create an innovative educational platform tailored for diverse learners. This project aims to develop a user-friendly website offering interactive learning resources, personalized study tools, and collaborative features. Key objectives include providing seamless navigation, curating diverse educational content, implementing adaptive learning algorithms, and fostering real-time collaboration among students and educators. Emphasizing scalability, compatibility, and security, the website seeks to empower learners globally with accessible, engaging, and personalized learning experiences, ultimately fostering academic excellence and lifelong learning opportunities.

Working of E-Ticketing for Public Buses

The transition from manual, cash-based ticketing procedures to a cutting-edge digital system represents a pivotal advancement in modernizing India's public bus transportation. This research paper delves into the working model of e-ticketing for public buses, aimed at addressing long-standing challenges of wait times, operational hurdles, and inefficiencies inherent in traditional systems. By leveraging state-of-the-art digital technology, this initiative aims to revolutionize the public transportation experience, enhancing security, convenience, and operational efficiency for both administrators and passengers. Thus, to provide an agile and smooth ticketing experience, we have proposed the smart application. [4] Key objectives of this research include the elimination of manual cash transactions, reduction of wait times, and mitigation of operational inefficiencies. Through the implementation of a digital ticketing system, the paper explores how transaction processes are streamlined, providing passengers with a seamless interface for ticket purchases. Not only does this innovation enhance transaction security, but it also fosters a more agile and responsive public bus transportation system. The research assesses the tangible benefits of the digital ticketing solution, highlighting its role in increasing passenger flexibility and reducing congestion through shorter wait times and improved traffic flow. Real-time data analytics are examined as a critical tool for administrators, enabling enhanced resource allocation and informed decision-making processes. This paper presents a comprehensive analysis of the working model of e-ticketing for public buses, offering insights into its functionality, implementation challenges, and the transformative impact it has on India's public transport sector. By promoting a more sophisticated and user-friendly framework, the research underscores the potential of digital ticketing solutions to redefine the landscape of public transportation, paving the way for a more efficient and accessible urban mobility system in India. Key Word: E-ticketing, Public buses, Digital technology, Operational efficiency, Urban mobility

REAL TIME AIR QUALITY PREDICTION AND ANOMALY DETECTION

When it comes to addressing the growing concerns about environmental health and safety, real-time air quality forecast and anomaly detection are essential. This study describes a robust system that effectively tracks, analyses, and forecasts air quality parameters in real-time using a combination of cutting-edge sensors, sophisticated data analytics, and machine learning algorithms. Utilising a wide range of environmental sensors, the system continuously monitors pollutants such as carbon monoxide, nitrogen dioxide, sulphur dioxide, particulate matter (PM2.5 and PM10), and ozone. Modern data analytics techniques are then used to process and analyse the gathered data. A machine learning platform at the centre of the system makes use of time-series forecasting methods to forecast air quality conditions. Additionally, it uses anomaly detection algorithms to identify anomalous trends or abrupt spikes in pollutant concentrations, which may indicate operational issues or environmental dangers. Environmental agencies and public health experts can take timely action and make informed judgements thanks to these skills. In addition, the system has an easy-to-use interface that provides both specialists and non-experts with real-time updates and visual representations of air quality statistics. Using IoT technology increases the system's expandability to larger regions and guarantees effective data flow. By providing consistent and accurate air quality information, this technique not only supports urgent mitigation measures but also facilitates strategic environmental and public health planning. Predictive analytics and proactive surveillance are intended to improve environmental governance and public health. Keywords—LSTM, Linear Regression and Minmax scalar.

Proposal of a Machine Learning Predictive Maintenance Solution Architecture

This article proposes an architecture model for a predictive maintenance solution that can be used to detect degradation of equipment in industrial units. This platform is compliant with Industry 4.0 standards and employs machine-learning algorithms alongside with data analytics methodologies to model the kinetics of equipment degradation. This serves the overarching aim of Industry 4.0 by enabling real-time, data-driven decision-making and complex asset management. To model the deterioration of the equipment, advanced data analysis techniques and machine learning were used, thus allowing for the early identification of imminent failures and reducing system downtime. The proposed solution was validated through numerous experiments and a comprehensive analysis of data. The results indicate not only enhanced operational reliability but also a reduction in environmental impact, thereby highlighting the value of intersecting Industry 4.0 and Sustainability paradigms in the field of industrial systems.

The impact of ambidextrous traditional and contemporary data analytics on marketing innovation

The impact of ambidextrous traditional and contemporary data analytics on marketing innovation

Challenges and directions for digital twin implementation in otorhinolaryngology.

Digital twin technology heralds a transformative era in Otorhinolaryngology (ORL), merging the physical and digital worlds to offer dynamic, virtual models of physical entities or processes. These models, capable of simulating, predicting, and optimizing real-world counterparts, are evolving from static replicas to intelligent, adaptive systems. Fueled by advancements in communication, sensor technology, big data analytics, Internet of Things (IoT), and simulation technologies, artificial intelligence (AI), digital twins in ORL promise personalized treatment planning, virtual experimentation, and therapeutic intervention optimization. Despite their potential, the integration of digital twins in ORL faces challenges including data privacy and security, data integration and interoperability, computational demands, model validation and accuracy, ethical and regulatory considerations, patient engagement, and cost and accessibility issues. Overcoming these challenges requires robust data protection measures, seamless data integration, substantial computational resources, rigorous validation studies, ethical transparency, patient education, and making the technology accessible and affordable. Looking ahead, the future of digital twins in ORL is bright, with advancements in AI and machine learning, omics data integration, real-time monitoring, virtual clinical trials, patient empowerment, seamless healthcare integration, longitudinal data analysis, and collaborative research. These developments promise to refine diagnostic and treatment strategies, enhance patient care, and facilitate more efficient and tailored ORL research, ultimately leading to more effective and personalized ORL management.

Solar-Powered GSM Irrigation for Intelligent Water Management

Efficient water management is crucial for sustainable agriculture and landscaping. This project introduces a novel solution, combining solar power and GSM technology to create an intelligent irrigation system. Integrated GSM connectivity enables remote monitoring and control, allowing users to adjust irrigation schedules and settings from anywhere, enhancing convenience and flexibility. By leveraging data analytics and sensor feedback, the system optimizes water usage, ensuring precise delivery based on plant needs and environmental conditions. This approach not only conserves water but also promotes healthier plant growth and higher yields. The integration of GSM technology ensures real-time communication and alerts, allowing users to respond promptly to changing conditions and unforeseen events. Through case studies and performance evaluations, the presentation will demonstrate the system's reliability, durability, and cost- effectiveness, underscoring its viability for widespread adoption. Attendees will gain insights into how solar- powered GSM irrigation can revolutionize water management practices, empower farmers and gardeners, and contribute to building resilient, sustainable ecosystems in a rapidly changing world.

Advancing Language Assessment and Evaluation: Innovative Strategies for Specialized English Teaching

This research paper examines the field of language assessment and evaluation. We shall primarily concentrate on the sophisticated techniques used in the specialized domain of English instruction. With the growing need for enhanced language training, educators are striving to enhance assessment techniques in order to precisely gauge language competency and provide focused instructional interventions. We acknowledge that the process of acquiring language is always evolving. Therefore, our study advocates for the use of adaptable and varied evaluation techniques that surpass conventional approaches. We are exploring the use of technology, artificial intelligence, and data analytics to develop customized assessment tools. These technologies would enable the assessment of individual student performance and provide targeted support for their unique learning requirements. Furthermore, the research explores the use of performance-based evaluations and proposes that instructors have to design activities that emulate authentic language scenarios. This strategy enhances the credibility of evaluations and provides vital insights into a learner's practical language application abilities. We use case studies and practical examples to demonstrate the effective implementation of these advanced tactics in various specialized English teaching contexts.

A streamlined workflow for a fast and cost-effective count of tyndallized probiotics using flow cytometry

The use of dead probiotics and their cellular metabolites seems to exhibit immunomodulatory and anti-inflammatory properties, providing protection against pathogens. These inanimate microorganisms, often referred to as tyndallized or heat-killed bacteria, are a new class of probiotics employed in clinical practice. Safety concerns regarding the extensive use of live microbial cells have increased interest in inactivated bacteria, as they could eliminate shelf-life problems and reduce the risks of microbial translocation and infection. Culture-dependent methods are not suitable for the quality assessment of these products, and alternative methods are needed for their quantification. To date, bacterial counting chambers and microscopy have been used for tyndallized bacteria enumeration, but no alternative validated methods are now available for commercial release. The aim of the present study is to design a new method for the qualitative and quantitative determination of tyndallized bacterial cells using flow cytometric technology. Using a live/dead viability assay based on two nucleic acid stains, thiazole orange (TO) and propidium iodide (PI), we optimized a workflow to evaluate bacterial viability beyond the reproduction capacity that provides information about the structural properties and metabolic activities of probiotics on FACSVerse without using beads as a reference. The data obtained in this study represent the first analytical application that works effectively both on viable and non-viable cells. The results provided consistent evidence, and different samples were analyzed using the same staining protocol and acquisition settings. No significant discrepancies were highlighted between the declared specification of commercial strain and the analytical data obtained. For the first time, flow cytometry was used for counting tyndallized bacterial cells as a quality control assessment in probiotic production. This aspect becomes important if applied to medical devices where we cannot boast metabolic but only mechanical activities.

How Do Innovative Improvements in Forensic Accounting and Its Related Technologies Sweeten Fraud Investigation and Prevention?

The purpose of this article is to look at recent developments in forensic accounting that have to do with preventing and investigating fraud. The following new developments in forensic accounting are being studied by doing a thorough literature review: data analytics, cyber forensic accounting, and the impact of blockchain and cryptocurrencies on the field. We take a close look at each new trend, breaking it down into its uses, pros, disadvantages, and ethical implications. Case studies and real-world examples back up the findings, showing how effective these fraud prevention and investigation tendencies are. Investigations into financial crimes employing information technology have their own set of challenges, which the report sheds light on. Blockchain technology’s capacity to increase accountability, traceability, and transparency in financial transactions is also explored. To improve fraud detection and prevention efforts, the study finishes with suggestions for researchers, practitioners, and policymakers to adapt to and take advantage of these new trends. To effectively identify and discourage financial crime in the constantly evolving world of new technology, the study finishes by stressing the necessity for continuous research and innovation, highlighting the dynamic character of forensic accounting.

Abstract PO3-10-06: Parenting While Living with Cancer - Providing Better Outcomes for Families During the Cancer Journey

Abstract For over 20 years, Kesem has been dedicated to supporting children impacted by a parent’s cancer. To better understand the stresses on a family navigating cancer, Kesem completed a several month research program rooted in Diversity, Equity, and Inclusion (DEI) and consisting of ethnographic research, quantitative surveys, focus groups, benchmarking, and data analytics. We are using this research to develop a deeper understanding of the personal stories of families impacted by a cancer diagnosis and of the current data from experts in the field. Kesem is sharing our research findings in order for the general oncology space to better serve parents living with cancer. The research included three weeks of ethnographic research completed in rural Mississippi, the Pacific Northwest, and southern Nevada. The research team completed 124 interviews in 18 cities, gathering deep insights about being a parent while living with cancer. The team also reviewed over 30 databases and conducted a survey of approximately 150 parents with cancer. Little has been published about parental cancer in the past decade. Using literature reviews and data such as the 2020 decennial census, we have been able to generate a more accurate assessment of need than ever, confirming earlier estimates that there are approximately five million children in the United States who have a parent with cancer. This means that the average percentage of children under 18 who have experience with parental cancer is between 3.6%–5.5%. The following key takeaways from this research are helpful for all who support patients, including oncologists, nurse navigators, and patient advocates: Based on this research and our ongoing internal survey results, we know that patients generally have less anxiety when they know their children will receive a lifetime of support. Children who are supported are more likely to create a community of support for themselves, do better academically, and have increased mental health. This leads to better outcomes for the entire family. Citation Format: Alicia Kabir. Parenting While Living with Cancer - Providing Better Outcomes for Families During the Cancer Journey [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-10-06.

How to improve firm performance using big data analytics capability and business strategy alignment

The current fascination with big data has some organizations make big data analytics activities to improve firm performance. Thus, regarding big data analytics capability, it might work for some companies but not for others. It seems that almost no one has made a significant difference through big data. To address this challenge, this study suggests a big data analytics capability model based on the resource-based theory and the entanglement view of socio-materialism. The results show the big data analytics capability hierarchy, which has three basic components (i.e., management, technology, and employee capability) and eleven subcomponents (i.e., planning, investment, coordinating, controlling, connectivity, compatibility, modularity, technology management skills, technical skills, business skills, and relational skills). Through Delphi studies together with online surveys of business analysts at the organization, the entanglement perspective of the high-order big data analytics capability model and its impact on firm performance was affirmed. This article investigates how organizations capitalize on big data analytics to create a sustainable competitive edge and progress business efficiency through big data analytics. On the other hand, the study delineates different resources and sub-capabilities which it takes to develop the big data analytics capability.

Untangling the cumulative impact of big data analytics, green lean six sigma and sustainable supply chain management on the economic performance of manufacturing organisations

Big data analytics provides up-to-date information to facilitate organisational decision-making and boost economic performance. However, an organisation’s big data analytical capability must be investigated to determine its importance in driving economic performance through continuous improvement and sustainability-related tools such as green lean six sigma and sustainable supply chain management. We conducted an empirical study and obtained 443 effective responses from managerial staff working in small and medium-sized organisations in Pakistan. Using structural equation modelling and artificial neural networks, we investigate the effects of big data analytics, green lean six sigma and sustainable supply chain management on economic performance. Our result shows that green lean six sigma and sustainable supply chain management partially mediate the relationship between big data analytics and economic performance. Although the implementation of sustainable supply chain management is identified, it is supported by technological but not cultural compatibility in the current operating environments of the organisations. As a theoretical contribution, this study enriches the literature on digitisation by relating it to the dynamic capability theory. As per practical contribution, this study reveals that the amalgamation of big data analytics, green lean six sigma, and sustainable supply chain management strengthen the organisation’s economic performance.

Practices and Challenges of Recruitment in IT Industry

One of the most The purpose of this thesis is to delve into the practices and challenges of recruitment within the IT industry, offering a comprehensive analysis of the strategies employed by recruiters and the obstacles they encounter. By examining the prevailing recruitment landscape, this research seeks to shed light on the complexities of talent acquisition in the IT sector and provide actionable insights for enhancing recruitment effectiveness. The IT industry is characterized by its reliance on highly skilled professionals who possess specialized technical expertise. As such, attracting and retaining talent with the requisite skills and experience is essential for driving innovation, meeting project deadlines, and delivering high-quality products and services. However, the demand for skilled IT professionals often outstrips the available supply, leading to talent shortages and intense competition among employers. To address these challenges, recruiters in the IT industry employ a variety of strategies, ranging from leveraging advanced recruitment technologies and data analytics to enhancing employer branding and implementing agile recruitment methodologies. By understanding the prevailing recruitment practices and challenges within the IT industry, organizations can develop tailored strategies to attract and retain top talent, thereby driving organizational growth and competitiveness. Through a combination of literature review, empirical research, and real-world case studies, this thesis aims to provide a comprehensive understanding of the practices and challenges of recruitment in the IT industry. By synthesizing theoretical insights with practical examples, this research seeks to offer valuable insights and actionable recommendations for recruiters, HR professionals, and organizational leaders seeking to optimize their recruitment efforts in the rapidly evolving IT landscape.

Big data analytics and environmental performance:The moderating role of internationalization

This study investigates the influence of big data analytics on environmental performance in the context of US Fortune 500 listed internationalizing companies from 2010 to 2021. Grounded in organizational learning theory, our results highlight BDA's positive impact, enabling firms to adapt and enhance environmental practices throughdata-driven insights. Furthermore, the study reveals the moderating role of internationalization, emphasizing the strategic management of knowledge and engagement with diverse stakeholders as pivotal factors in enhancing the positive influence of BDA on environmental performance. These findings offer valuable insights for organizations leveraging data analytics to address environmental challenges in the global business landscape.

An efficient test suit reduction methodology for regression testing

<span lang="EN-US">This paper's goal is to provide a more effective algorithm for reducing the amount of test cases in a test suit during the regression testing phase. This algorithm divide the entire test suit into equivalence classes in first step and then apply boundary value coverage to select test case out of repeated test cases which has same importance in test suit. This algorithm is based on the concept that before selecting best test cases out of repeated test case in test suit to prepare reduced test suit we can divide all test cases in number of equivalence classes so number of test case under consideration reduced by great extend. This paper proposed a method of experimentation involving test cases from different software application areas; minimization algorithms and the maths and algorithms of minimization algorithms in details. Test case techniques are equivalence portioning and boundary value analysis. Along with this concept, I also discuss a case study to verify and check new algorithm for its efficiency, for that I apply my algorithm on one of the program or group of program. This complete proposed methodology shall be applied to different software applications belonging to soft computing, Engineering software, Financial Software, Cloud Applications, Business Applications, AI and Machine Learning, Data Analytics are being identified. This selection has been made keeping in mind the trends, industrial importance, economic values and research challenges. Minimization in test cases would lead to lesser testing effort and desirable test completion.</span>

Biological Potential and Therapeutic Effectiveness of Hinokiflavone in Medicine: The Effective Components of Herbal Medicines for Treatment of Cancers and Associated Complications

Background: Plants have been providing us medicines and food material for centuries. Traditional system of medicine, including Ayurveda, and Traditional Chinese medicines have been playing important role in health sectors for the treatment of human disorders since very early age. Plant secondary metabolites, including flavonoids, coumarins, saponins, and tannins have significant therapeutic potential in medicine. Biflavonoids are dimers of flavonoids, linked by a C–O–C or C–C bond. Hinokiflavone is an important class of biflavonoids found to be present in Toxicodendron succedaneum, Isophysis tasmanica, Juniperus rigida, Juniperus phoenicea, Platycladi cacumen, Rhus succedanea, Selaginella tamariscina, Platycladus orientalis, Selaginella bryopteris, and Metasequoia glyptostroboides. Methods: Biological potential of hinokiflavone in medicine have been analyzed in the present work through scientific data analysis of various literature work. Scientific database, including Google, Scopus, Science Direct, and PubMed were searched to collect all the scientific information of the present work using terms flavonoid, biflavonoid, herbal medicine, and hinokiflavone. Pharmacological activities of hinokiflavone were analyzed in the present work in very detailed manner. Analytical data of hinokiflavone were collected and analyzed in present work in order to know the biological source of hinokiflavone. Results: Present work signified the biological importance of hinokiflavone against various types of cancerous disorders, including breast cancer, colorectal cancer, esophageal squamous cancer, adenocarcinoma, hepatocellular carcinoma, myeloid leukemia, and melanoma. Further, its antiinflammatory, hepatoprotective, anti-viral, and anti-oxidant potential were also discussed in the present work. Moreover, its biological potential against COVID-19 and hair loss, and procoagulant activity were also summarized in this paper. Analytical data on hinokiflavone signified the importance of various analytical techniques in the extraction, separation, and identification of hinokiflavone with their pharmacokinetic parameters. Conclusion: Present work signified the biological importance and therapeutic potential of hinokiflavone in medicine.