International Journal of Unique and New Updates, ISSN: 3079-4722
The International Journal of Unique and New Updates (IJUNU), ISSN: 3079-4722 is an innovative, peer-reviewed journal dedicated to showcasing groundbreaking discoveries, emerging trends, and transformative ideas across a broad spectrum of disciplines. Published by Octopus Publication, Hong Kong, IJUNU serves as a global platform for researchers, professionals, and thought leaders to share pioneering insights and novel advancements that redefine the frontiers of knowledge. Our mission is to provide a dynamic space for the publication of unique studies and cutting-edge updates that push the boundaries of conventional research. The journal welcomes contributions from all fields, with a special focus on: Breakthrough innovations and technologies Novel methodologies and applications Emerging disciplines and interdisciplinary research Transformative studies shaping future trends Updates on critical advancements in science, technology, and societal development At IJUNU, we are committed to excellence, originality, and relevance. By fostering international collaboration and disseminating high-impact research, we aim to inspire innovation and drive meaningful contributions to the global knowledge economy. Here are some basic details of IJUNU : IJUNU : International Journal of Unique and New Updates ISSN: 3079-4722 Chief Editor: Dr. David M. Jones, UK Publisher: Octopus Publication, Hong Kong Starting Year: 2019 Frequency: Half Yearly [2 issues per year] Languages: Multiple Languages Accessibility: Open Access Crossref DOI Prefix: 10.XXXXXX Copyright : IJUNU Journal, Hong Kong Peer Review Process: Double Blind Peer Review Process Subject: Multidisciplinary Plagiarism Checker: Turnitin Publication Format: Online Contact No.: +852-96752508 Email: info@octopuspublication.com Website: https://ijunu.com Address : 10 Wai Tsui Crescent, Braemar Hill, North Point, Hong Kong 000000 Hongkong, H.K.S.A.R. Key Features of IJUNU Journal listed in Google Scholar Indexed with Crossref DOI Journal Publishes online on continuous basis Online article submission Standard peer review process
Electrochemical Sensors for Biomedical and Environmental Monitoring: A Comprehensive Review
Electrochemical sensors have emerged as powerful analytical tools for real-time monitoring in biomedical diagnostics and environmental surveillance due to their high sensitivity, selectivity, rapid response, and cost effectiveness. These sensors operate by converting chemical information into measurable electrical signals through electrochemical reactions occurring at the electrode–electrolyte interface. In recent years, significant advancements in nanomaterials, electrode modification techniques, and microfabrication technologies have greatly enhanced the performance and applicability of electrochemical sensing platforms.
Electrochemical Sensors, Biomedical Monitoring, Environmental Monitoring, Nanomaterial-Based Sensors, Biosensing Technologies
Inverse Optimization: A Case Study in Supply Chain Cost Estimation
Determining unknown parameters of an optimization model such that a given feasible solution becomes optimal is the focus of the quickly emerging discipline of inverse optimization in operations research. Inverse optimization infers model coefficients from observed decisions, in contrast to traditional optimization, which seeks the optimal solution for the given know parameters. This Paper demonstrate the implementation of inverse optimization through a case study in supply chain cost estimation. The inverse problem is developed to extract transportation cost coefficients from observable shipping patterns using a linear programming transportation model. The formulation in mathematics, the method of solving it, and the computing example are presented. The paper emphasises how inverse optimization is useful in decision sciences, logistics, energy systems, and economics.
Inverse optimization, inverse linear programming, supply chain, cost estimation, transportation problem.
Organotellurium-Mediated Radical Polymerization (TERP)
Controlled radical polymerization, also known as living radical polymerization, has made significant advances during the last three decades and has revolutionized the development of polymeric materials. While atom transfer radical polymerization (ATRP) and reversible addition-fragmentation chain transfer polymerization (RAFT) are the most popular methods, it has independently developed organotellurium-mediated radical polymerization (TERP) and have implemented it in society through industry-academic collaborations.
controlled radical polymerization, reversible deactivation radical polymerization, tellurium, hyperbranched
Regenerative Endodontics in Children: Current Evidence, Challenges, and Future Directions
The management of immature permanent teeth with necrotic pulps presents a significant challenge in paediatric endodontics, due to incomplete root formation, thin dentinal walls, and vulnerability to fracture. Traditional methods (e.g., apexification) promote apical closure but do not restore the functional pulp–dentin complex or allow for continued root maturation.
regenerative endodontics; immature permanent teeth; paediatric endodontics; stem cells; pulp regeneration; root maturation.
Dr. Asha Rani, Dr. Nisha Yadav, Dr. Anisha Kakran
Modernization of Industrial Legacy Control Systems: Migration Strategies, Risk Mitigation, and Operational Continuity in Critical Infrastructures
The modernization of industrial legacy control systems is a pressing requirement in the era of Industry 4.0, as aging infrastructures increasingly hinder scalability, interoperability, and cybersecurity resilience.
Legacy control systems, migration strategies, risk mitigation, operational continuity, critical infrastructure.
The Decline of Feudal Structures and Rise of Urban Aspirations in Mahesh Elkunchwar’s Wada Trilogy: A Postcolonial and Marxist Analysis
This research paper critically analyses Mahesh Elkunchwar’s Wada Trilogy—Wada Chirebandi, Magna Talyakathi, and Yugant—to examine the decline of feudal structures and the rise of urban aspirations in post independence India.
Mahesh Elkunchwar; Wada Trilogy; Postcolonial analysis; Marxist criticism; Feudal decline; Urban aspirations; Generational conflict; Cultural displacemen
Vishwajit Marotrao Kowase, Dr. S M Warkad
Reinforcement Learning Algorithms for Optimizing Traffic Flow in Smart City Infrastructures
The rapid growth of urban populations and increasing vehicular traffic necessitate innovative solutions for optimizing traffic flow within smart city infrastructures. This paper explores the application of reinforcement learning (RL) algorithms to address these challenges by dynamically adjusting traffic signal timings, rerouting vehicles, and managing congestion. We present an overview of various RL techniques, such as Q-learning, Deep Q Networks (DQN), and policy gradient methods, emphasizing their ability to adapt to real-time traffic conditions and improve system efficiency. The study evaluates RL-based approaches through simulations and case studies, demonstrating their potential to reduce travel times, lower emissions, and enhance the overall sustainability of urban transport networks. Moreover, we discuss the integration of RL algorithms with emerging technologies such as the Internet of Things (IoT), autonomous vehicles, and edge computing to create responsive, data-driven traffic management systems. The findings suggest that reinforcement learning can significantly enhance traffic optimization in smart cities, providing a scalable and flexible framework for future intelligent transportation systems.
Reinforcement Learning, Machine Learning, Traffic Optimization, Smart City Infrastructure, Intelligent Transportation Systems.
Tourism Finance And Temple Economics: Shaping India’s Religious Tourism Landscape
This paper explores the intricate relationship between tourism finance and temple economics in shaping India’s religious tourism landscape. India, a country rich in spiritual heritage and diverse religious practices, attracts millions of domestic and international tourists annually to its temples. However, the financial dynamics surrounding temple tourism remain underexplored. By examining various funding models employed by religious institutions, public-private partnerships, and government initiatives, this study illustrates how financial strategies fundamentally impact infrastructure development, visitor services, and spiritual experiences. Furthermore, it delves into the socio-economic implications of temple-based tourism on local communities, including job creation, community development, and cultural preservation. The findings reveal that sustainable financing mechanisms not only enhance the viability of religious tourism but also ensure the preservation of cultural heritage and local ecosystems. Ultimately, this analysis offers recommendations for policymakers, religious authorities, and tourism operators to collaboratively enhance the sector's growth, ensuring it aligns with broader development goals. By bridging the gap between tourism finance and temple economics, this paper contributes to a better understanding of how religious tourism can be leveraged to promote economic prosperity while respecting India's rich spiritual traditions.
A New Preconditioned Gauss-Seidel Method faster than the Classical Gauss-Seidel Method
Due to this when is large and sparse, iterative methods are very much essential for solving the linear system (1). Moreover, when the condition number of the coefficient matrix is large then the iterative methods converge very slowly.
The Role of AI in Shaping Future it Investments
The integration of artificial intelligence (AI) in investment decision-making has revolutionized the financial landscape, enhancing data processing, predictive accuracy, and risk assessment. However, human expertise remains essential to contextualize AI-driven insights, ensuring ethical considerations, adaptability, and transparency. This paper explores the collaboration between AI and human intelligence in optimizing investment strategies, balancing automation with human judgment, and improving decision-making frameworks. AI’s capabilities in data analytics, real-time market forecasting, and personalized investment strategies offer financial institutions a competitive edge, while human oversight mitigates risks associated with algorithmic biases and regulatory compliance. By fostering synergy between AI-powered systems and financial professionals, institutions can navigate market complexities efficiently, ensuring strategic resilience.
Artificial Intelligence, Investment Decision-Making, Financial Markets, Risk Management, Algorithmic Transparency
Cybersecurity Measures for Application: Protecting against Vulnerabilities
Applications need to be protected from evolving threats including malware, phishing, and data breaches by applying the cyber essentials. This study is based on secondary research for analyzing the common vulnerabilities, security measures, regulatory frameworks and emerging technologies. According to the findings, application security is better if encryption is used, if multiple factors of authentication are supported and if the application complies with standards like GDPR and ISO 27001. It also shows the effectiveness of emerging solutions, including artificial intelligence, and zero-trust security models. For long-term protection, you need to practice secure coding and proactive threat detection. Considering the ever-increasing rate of advancement in cyber threats, it becomes increasingly important to continue research and innovation of more resilient security strategies for app development.
Cybersecurity, Application Security, Data Protection, Cyber Threats, Encryption, Multi-Factor Authentication, Regulatory Compliance
DevOps Best Practices: Automating Deployment for Faster Delivery
The rise of DevOps has revolutionized software development and delivery, emphasizing collaboration, speed, and reliability. Deployment automation, a cornerstone of DevOps, enables faster, more efficient software delivery while reducing manual errors and ensuring consistent deployments. This paper explores the evolution of DevOps and deployment automation, highlights foundational practices like Continuous Integration (CI) and Infrastructure as Code (IaC), and provides insights into key automation tools and frameworks. Additionally, it examines CI/CD pipeline architecture, automated testing, monitoring, and future trends such as AI-driven automation. The research concludes with actionable recommendations to enhance deployment automation for DevOps practitioners.
DevOps, Continuous Integration, Continuous Deployment, CI/CD Pipeline, Automation, Infrastructure as Code, Deployment Automation, DevSecOps
Nutritional Science and Personalized Diets: A New Era of Health Research
The rapid advancements in nutritional science and the growing awareness of the impact of diet on health have sparked a shift towards personalized nutrition, marking the beginning of a new era in health research. This paper explores the transformative potential of personalized diets, which leverage individual genetic, metabolic, and microbiome data to optimize health outcomes. It examines the role of emerging technologies such as nutrigenomics, metabolomics, and microbiome sequencing in tailoring dietary recommendations to the unique needs of individuals. By integrating these insights into clinical practice, personalized diets promise to enhance the prevention and management of chronic diseases, improve overall wellness, and address the limitations of one-size-fits-all dietary guidelines. The paper also highlights challenges in implementation, ethical considerations, and the need for large-scale studies to validate personalized nutrition interventions. In conclusion, personalized diets represent a paradigm shift in nutritional science, offering a more precise and individualized approach to health, while fostering new opportunities for innovation in medical nutrition therapy.
Media and Misinformation: The Role of Scholars in Combating Fake News
The proliferation of misinformation and fake news in the digital age has emerged as a significant challenge to society, influencing public opinion, policy, and individual behaviors. With the widespread use of social media platforms and online news outlets, the spread of false information has become faster and more pervasive, often leaving the public vulnerable to misleading narratives. This paper explores the role of scholars in combating misinformation by providing expertise in media literacy, critical thinking, and the verification of news sources. It examines the intersection of academic research, journalistic ethics, and the public's consumption of media, highlighting how scholars can contribute to mitigating the adverse effects of fake news. Through interdisciplinary efforts, scholars can promote educational initiatives, develop tools for identifying credible information, and advocate for more rigorous journalistic standards. The paper also investigates the responsibilities of academia in fostering an informed citizenry and shaping policies that address the ethical concerns surrounding media and misinformation. In conclusion, the involvement of scholars is crucial in the collective effort to combat fake news and enhance media integrity in an increasingly complex information environment.
Artificial Intelligence and the Future of Ethics in Social Sciences
Artificial Intelligence (AI) is rapidly transforming the landscape of the social sciences, bringing both opportunities and challenges to the field. As AI technologies become more integrated into research, policy-making, and everyday social interactions, they raise fundamental ethical questions that require careful examination. This paper explores the implications of AI on ethics in social sciences, focusing on issues such as bias, privacy, accountability, and the potential for discrimination in algorithmic decision-making. The evolving nature of AI demands a rethinking of traditional ethical frameworks to ensure that technology serves humanity equitably and justly. The paper examines how AI can influence social science methodologies, shaping new approaches to data collection, analysis, and prediction. Additionally, it discusses the role of interdisciplinary collaboration between technologists, ethicists, and social scientists in developing AI systems that prioritize fairness, transparency, and social responsibility. Finally, the paper suggests that proactive engagement with these ethical challenges is essential for the sustainable and ethical integration of AI in the social sciences, ensuring that future advancements align with human values and social equity.
The Internet of Things (IoT) in Academic and Industrial Research
The Internet of Things (IoT) has emerged as a transformative technology, offering vast potential in both academic and industrial research domains. IoT refers to the interconnected network of physical devices embedded with sensors, software, and other technologies to collect, exchange, and analyze data. This paper explores the application of IoT in academic and industrial research, highlighting its role in enhancing data-driven decision-making, optimizing operational processes, and enabling real-time monitoring. In academia, IoT is reshaping research methodologies, allowing for innovative experiments, smarter data collection techniques, and interdisciplinary collaboration. In the industrial sector, IoT is driving advancements in automation, supply chain management, predictive maintenance, and energy efficiency. This research also examines the challenges IoT presents, such as security concerns, data privacy issues, and the integration of disparate systems. The paper concludes by emphasizing the need for continued research into IoT infrastructure, standards, and governance to unlock its full potential across various sectors.
Human-Computer Interaction: Enhancing User Experience in AI Systems
Human-Computer Interaction (HCI) plays a crucial role in shaping the usability, accessibility, and overall experience of AI-driven systems. As artificial intelligence continues to advance, designing intuitive and user-centric interfaces becomes essential to maximize engagement, efficiency, and trust. This paper explores the fundamental principles of HCI in AI systems, highlighting key factors such as adaptive interfaces, natural language processing, personalization, and ethical considerations. It also discusses challenges related to cognitive load, bias, and transparency, emphasizing the need for user-friendly designs that promote seamless human-AI collaboration. By integrating HCI best practices, AI systems can be tailored to diverse user needs, enhancing usability and fostering positive interactions. The study concludes with recommendations for future research and development aimed at optimizing user experience in AI-driven applications.
The Role of Space Research in Advancing Earth Science and Sustainability
Space research has revolutionized our understanding of Earth by providing critical insights into climate change, natural disasters, resource management, and environmental sustainability. Satellites and space-based technologies enable precise monitoring of atmospheric conditions, ocean currents, deforestation, and greenhouse gas emissions, offering invaluable data for scientific analysis and policy-making. Remote sensing, GPS, and Earth observation programs contribute to disaster prediction, mitigation, and response, enhancing global resilience to environmental challenges. Moreover, advancements in space technology drive innovations in energy efficiency, water conservation, and sustainable agriculture, fostering a more sustainable future. This paper explores the intersection of space research and Earth science, highlighting its role in addressing global environmental concerns and shaping policies for long-term ecological balance. Through continued investment and collaboration in space research, humanity can achieve sustainable development while safeguarding the planet for future generations.
Renewable Energy Technologies and Their Impact on Climate Change Mitigation
Renewable energy technologies play a crucial role in mitigating climate change by reducing greenhouse gas emissions and decreasing reliance on fossil fuels. This paper explores key renewable energy sources, including solar, wind, hydro, biomass, and geothermal energy, highlighting their advancements, efficiency, and environmental benefits. The transition to renewable energy not only lowers carbon footprints but also enhances energy security and promotes sustainable economic growth. However, challenges such as high initial costs, energy storage limitations, and infrastructure development must be addressed to maximize their potential. Through policy support, technological innovation, and global cooperation, renewable energy can significantly contribute to achieving climate goals, such as those outlined in the Paris Agreement. This study underscores the necessity of accelerating the adoption of renewable technologies to combat climate change and ensure a cleaner, more sustainable future.
The Rise of Bioinformatics: Transforming Research in Life Sciences
Bioinformatics has emerged as a transformative field in life sciences, integrating computational techniques with biological data to drive scientific discovery. The exponential growth of genomic, proteomic, and metabolomic data has necessitated advanced algorithms, machine learning, and big data analytics to process and interpret complex biological information. This interdisciplinary approach has revolutionized areas such as personalized medicine, drug discovery, and evolutionary biology, enabling researchers to uncover novel insights with unprecedented speed and accuracy. The rise of bioinformatics has also facilitated large-scale collaborations, open-access data sharing, and automation in research, accelerating innovation in disease diagnostics and treatment. As computational power continues to evolve, bioinformatics is poised to play an even greater role in shaping the future of life sciences, offering new opportunities and challenges in managing and analyzing vast biological datasets.
The Role of Citizen Science in Advancing Academic Research
Citizen science, the collaboration between professional researchers and the general public, has emerged as a powerful tool for advancing academic research across various disciplines. By leveraging the collective efforts of volunteers, citizen science enhances data collection, expands research scope, and accelerates scientific discovery. This paper explores the key contributions of citizen science in fields such as environmental monitoring, astronomy, health sciences, and biodiversity conservation. It highlights the benefits of increased public engagement, cost-effective data acquisition, and improved scientific literacy while also addressing challenges such as data reliability and ethical considerations. Through case studies of successful citizen science projects, this study underscores its transformative potential in bridging the gap between academia and society. Ultimately, the integration of citizen science into mainstream research frameworks fosters inclusivity, democratizes knowledge production, and strengthens scientific outcomes.
Emerging Trends in Interdisciplinary Research: Challenges and Opportunities
Interdisciplinary research is increasingly shaping the landscape of scientific and technological advancements, driving innovation by integrating diverse fields of knowledge. This paper explores emerging trends in interdisciplinary research, highlighting its transformative potential in addressing complex global challenges such as climate change, healthcare, artificial intelligence, and sustainable development. Advances in data science, biotechnology, and computational modeling have facilitated collaboration across disciplines, enabling new discoveries and applications. However, interdisciplinary research also faces significant challenges, including communication barriers, methodological integration, funding constraints, and institutional resistance. This paper examines these challenges and discusses strategies for fostering successful interdisciplinary collaborations. By leveraging cross-disciplinary expertise, fostering open innovation ecosystems, and addressing structural barriers, interdisciplinary research can unlock novel opportunities for scientific progress and societal impact.
The Evolution of Peer Review Systems in Modern Academic Publishing
The evolution of peer review systems in modern academic publishing has been marked by significant advancements, aimed at enhancing the integrity, quality, and transparency of scholarly communication. Initially, peer review emerged as a crucial mechanism to ensure the accuracy and reliability of published research. Over time, the process has evolved to adapt to the growing volume of academic publications, the diversity of disciplines, and the advent of digital platforms. Traditionally, peer review was anonymous and limited in scope, with experts in the field evaluating the merits of submitted manuscripts. However, modern systems have diversified, incorporating open peer review, post-publication review, and collaborative platforms that encourage greater transparency and accessibility. These changes have been driven by the need to address concerns such as bias, delays, and the pressure to publish. Additionally, the rise of preprints and the global reach of online journals have prompted further modifications to peer review processes, allowing for more timely feedback and wider engagement. Despite these innovations, challenges remain, including the potential for increased workload on reviewers, conflicts of interest, and the balancing of speed with thorough evaluation. The future of peer review systems will likely continue to evolve, with increasing calls for more inclusive, transparent, and efficient processes that align with the changing landscape of academic publishing.
Navigating the Landscape of Kubernetes Security Threats and Challenges
Kubernetes has become the new standard for container orchestration, where it allows such organizations to manage applications. Alas, these features make it quite difficult to secure the containerized workloads, primarily this is due to its distributed nature and complexity that inherently poses multiple security threats. This paper aims to provide an overview on how Kubernetes works more specifically about the API Server, the Scheduler and the Controller Manager but also to discuss about the integrated security mechanisms such as the RBAC or Network Policies. Some of the threat categories discussed in detail are misconfiguration threats, container threats, network-oriented attacks, attacks on API servers, and supply chain attacks. This research elaborates on how these vulnerabilities appear, how they affect Kubernetes environments, and ways of preventing such, such as implementing strong configurations, encryption, constant monitoring, as well as dependency control. Through such aspects, this work highlights the need for incorporating active multidimensional approach to security to counter new threats. The insights presented herein are intended to assist organizations using Kubernetes to derive practical knowledge of methods to protect containerized applications while preventing and mitigating modern security threats.
Cross-Cultural Marketing Strategies for Rubber Products in Emerging Economies
This report explores cross-cultural marketing strategies for rubber products in emerging economies based on differences in culture, economy, and regulation. In the growing rubber industry across the world, emerging markets like Southeast Asia are massive opportunities that require specific approaches to marketing. The communication barrier and cultural differences regarding consumer behavior are some of the most important challenges facing marketers in such markets. Also, differences in the economy. This paper discusses localization, brand trust, and prestige sensitivity; it underlines the role of local preference knowledge for a firm. Forming local partnerships, adaptation to product offerings, and usage of digital marketing strategies is being discussed. Sustainability and the importance of digital transformation have also gained significance in the markets. By addressing such cultural dynamics, companies can thrive in the complexity of the emerging economies and achieve long-term success in the global rubber product market.
Edge Computing in IoT: Enhancing Real-Time Data Processing and Decision Making in Cyber-Physical Systems
The rapid proliferation of Internet of Things (IoT) devices has led to an exponential increase in data generation, necessitating new approaches to data processing and analysis. This manuscript explores the integration of edge computing within IoT frameworks, specifically focusing on its role in enhancing real-time data processing and decision-making in cyber-physical systems (CPS). By decentralizing data processing to the edge of the network, we can mitigate the latency, bandwidth, and privacy challenges associated with cloud-based solutions. The paper investigates various edge computing architectures and their applications across diverse sectors, including smart manufacturing, healthcare, and smart cities. Through case studies and empirical data, we demonstrate how edge computing not only improves response times and resource efficiency but also supports state-of-the-art machine learning algorithms designed for deployment in resource-constrained environments. The findings suggest that adopting edge computing in IoT ecosystems significantly enhances the operational capabilities of CPS, ultimately leading to smarter, more resilient systems adapted to real-time demands. This research lays the groundwork for future innovations in IoT and CPS integration, fostering advancements that leverage the full potential of connected environments.
Edge Computing; Internet of Things (IoT); Cyber-Physical Systems (CPS); Real-Time Processing; Decentralized Architecture.
Govindaiah Simuni, Mitesh Sinha, Reddy Srikanth Madhuranthakam, Ganesh Vadlakonda
Federated Learning for IoT: A Decentralized Approach to Enhance Privacy and Efficiency in Cyber-Physical Systems
The rapid proliferation of Internet of Things (IoT) devices has revolutionized cyber-physical systems, enabling a myriad of applications ranging from smart cities to health monitoring. However, the centralized data processing approaches that often underpin these systems raise significant concerns regarding user privacy, data security, and inefficient resource utilization [1][2]. This manuscript presents a comprehensive exploration of Federated Learning (FL) as a decentralized approach to address these challenges. We elucidate the conceptual framework of FL, highlighting its ability to facilitate collaborative model training across multiple IoT devices without the need for raw data to leave their local environments. This preserves the confidentiality of sensitive information while still enabling the generation of robust machine learning models. We detail the implementation of FL in various domains of IoT, showcasing its potential to enhance efficiency by leveraging the computational power of edge devices [3].
Federated Learning; Internet of Things (IoT); Privacy; Cyber-Physical Systems; Decentralized Approach
Ganesh Vadlakonda, Govindaiah Simuni, Mitesh Sinha, Reddy Srikanth Madhuranthakam
Securing the Smart Grid: Integrating Blockchain Technology for Cyber-Physical Systems in Energy Management
The burgeoning complexity and interconnectivity inherent in modern Smart Grid systems elevate their susceptibility to cyber threats, demanding robust and innovative security measures. This paper investigates the integration of blockchain technology—a decentralized and immutable ledger system—into smart grids, aiming to bolster the security and operational resilience of cyber-physical systems (CPS) used for energy management. Blockchain’s attributes, such as enhanced data integrity, transparency, and secure energy transactions, offer promising solutions to address prevalent security and efficiency challenges within smart grids. This paper highlights technological advancements in blockchain applications, potential obstacles, ongoing implementations, and future research directions critical for optimizing its role in securing smart grid infrastructures.
Blockchain Technology; Smart Grid; Cyber-Physical Systems; Energy Management; Security.
Reddy Srikanth Madhuranthakam, Ganesh Vadlakonda, Govindaiah Simuni, Mitesh Sinha
Digital Twins and Their Impact on Predictive Maintenance in IoT-Driven Cyber-Physical Systems
This research paper explores the transformative role of digital twin technology in enhancing predictive maintenance practices within Internet of Things (IoT)-driven cyber-physical systems (CPS). As industries increasingly adopt IoT solutions, the complexity and interconnectivity of physical assets necessitate innovative maintenance strategies aimed at minimizing downtime and optimizing operational efficiency [1]. Digital twins, which are virtual representations of physical entities, facilitate real-time monitoring, simulation, and predictive analytics by leveraging data from connected sensors [4][34].This study first provides a comprehensive overview of the digital twin concept, detailing its architecture, integration with IoT frameworks, and capabilities for data assimilation and analytics. It then delineates the relationship between digital twins and predictive maintenance, underscoring how these virtual models can predict equipment failures by analysing historical and real-time operational data [2][10].
Digital Twins; Predictive Maintenance; Internet of Things (IoT); Cyber-Physical Systems (CPS); Data Analytics
Mitesh Sinha, Reddy Srikanth Madhuranthakam, Ganesh Vadlakonda, Govindaiah Simuni
Drug-Device Combination Products: Design, Development and Regulatory Considerations
Drug-device combination products represent a significant and evolving segment within the healthcare industry, offering novel therapeutic approaches and enhanced patient care. This abstract delves into the multifaceted landscape of designing, developing, and regulating such products. The design phase of drug-device combination products demands a comprehensive understanding of both pharmaceutical and engineering principles. It necessitates seamless integration of drug substances with medical devices, ensuring compatibility, stability, and efficacy.
Drug-device combination products, Design, Development, Regulatory considerations, Healthcare industry.