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In the era of sharing economy, the tourism market is increasingly characterized by personalized demand, mobile consumption and product segmentation. This paper aims to apply big data mining technology in the field of smart tourism. Firstly, it focuses on image summary selection and collaborative filtering technology based on big data mining. It then demonstrates the integration of blockchain in smart tourism, emphasizing the use of decentralized structures and smart contracts to achieve data security and transparency, and describes the testing process of smart tourism platforms, including data preparation and platform operational efficiency testing. Finally, the research results of this paper are summarized, and the development potential and practical application value of smart tourism are demonstrated. The results show that in the smart tourism big data mining model, the minimum support for the data set is 10 % and 20 %, respectively. Moreover, with the increase of the number of nodes in the same data set, the running time decreases gradually. It can be seen that smart tourism big data mining has strong scalability.
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This study conducts a comprehensive analysis on the usage of the blockchain technology in clinical trials, based on a curated corpus of 107 scientific articles from the year 2016 through the first quarter of 2024. Utilizing a methodological framework that integrates bibliometric analysis, network analysis, thematic mapping, and latent Dirichlet allocation, the study explores the terrain and prospective developments within this usage based on data analytics. Through a meticulous examination of the analyzed articles, the present study identifies seven key thematic areas, highlighting the diverse applications and interdisciplinary nature of blockchain in clinical trials. Our findings reveal blockchain capability to enhance data management, participant consent processes, as well as overall trial transparency, efficiency, and security. Additionally, the investigation discloses the emerging synergy between blockchain and advanced technologies, such as artificial intelligence and federated learning, proposing innovative directions for improving clinical research methodologies. Our study underscores the collaborative efforts in dealing with the complexities of integrating blockchain into the areas of clinical trials and healthcare, delineating the transformative potential of blockchain technology in revolutionizing these areas by addressing challenges and promoting practices of efficient, secure, and transparent research. The delineated themes and networks of collaboration provide a blueprint for future inquiry, showing the importance of empirical research to narrow the gap between theoretical promise and practical implementation.
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Bibliometrics , Blockchain , Clinical Trials as Topic , Humans , Artificial Intelligence , Data ScienceABSTRACT
This paper explores how digital entrepreneurs' intention toward blockchain technology adoption, perception of reduced costs, and knowledge of Artificial Intelligence impact achieving UN's Sustainable Development Goals (SDGs), drawing attention from various sectors. Present study applies explanatory sequential mixed method for data collection. Moreover, to work with the dual face patterned data, PLS-SEM is used to perform quantitative analysis of the data collected from 389 digital entrepreneurs who are chosen through purposive sampling and then content analysis is performed for the qualitative data according to the explanatory sequential mixed method's rule of thumb. The study's quantitative phase shows that factors such as perceived ease of use and usefulness of Industry 4.0 technologies, knowledge of artificial intelligence (KAI), and perception of reduced cost positively influence digital entrepreneurs' intention to adopt blockchain technology (BCT). Notably, KAI has the strongest impact. In the qualitative phase, it's found that digital entrepreneurs' KAI and willingness to adopt BCT strongly align with achieving several UN Sustainable Development Goals (SDGs), suggesting BCT adoption's potential for sustainable outcomes. The outcomes of this study set a new benchmark in the domain of SDGs achievement with careful integration to Industry 4.0, AI and BCT. This study results undoubtedly instigate the digital entrepreneurs to adopt BCT in doing their start-up and convince the policymakers to set regulatory landscape with convenient environment for the utilization of BCT which then ultimately accelerates the achievement of SDGs.
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This paper aims to critically examine the scholarly work conducted in blockchain (BC) governance. Without venturing into the wide range of governance paradigms, this research considers governance structures based on trust as a foundation for BC governance. A thematic systematic literature review is conducted to understand the literature on this topic, employing the SALSA (Search, Appraisal, Synthesis and Analysis) technique. An examination of 155 papers shows that using BC technology (BCT) replaces the cognitive attribution of trust in the material and human-independent code. It is also found that further research anchored to the 'trust' concept is required in building BC governance structures. To provide the direction in which the literature is travelling, future research questions on trust and governance are documented. In general, the literature review suggests that BC has the potential to revolutionize the way in which businesses operate. By improving transparency, efficiency, and security, BC can help businesses to reduce costs, improve customer satisfaction, and make better decisions. This research can help policymakers, industrialists, and researchers to identify where BC governance is being used and which aspects of governance are to be focused on. This paper is a general review of literature and evidence on contemporary developmental issues.
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BACKGROUND: Blockchain technology provides a secure and decentralized platform for storing and transferring sensitive medical data, which can be utilized to enable remote medical consultations. AIM: A theoretical framework for creating a blockchain-based digital system created to facilitate telemedicine system. RESULTS: This paper proposes a theoretical framework based on Hyperledger fabric for creating a blockchain-based digital entity to facilitate telemedicine services. The proposed framework utilizes blockchain technology to provide a secure and reliable platform for medical practitioners to interact remotely with patient transactions. CONCLUSION: The blockchain will serve as a one-stop digital service to secure patient data, ensure privacy, and facilitate payments. The proposed framework leverages the existing Hyperledger fabric platform to build a secure blockchain-assisted telemedicine platform.
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AIM AND OBJECTIVE: This study aims to scrutinize the interconnected concepts, prevailing landscape and efficacy of personalized nursing within the framework of blockchain technology and to proffer a roadmap for prospective scholarly inquiries. BACKGROUND: The ethos of personalized nursing as a paradigm grounded in human-centered care has been venerated as the pinnacle of nursing practice. Recent years have witnessed the emergence of groundbreaking technologies, notably blockchain, which have set the stage for the actualization of personalized nursing care. Nevertheless, a lacuna persists in the holistic comprehension surrounding the integration of blockchain technology within the domain of personalized nursing. DESIGN AND METHODS: We considered studies published in English from 2018 to the present. Databases searched included CINAHL, Pubmed, MEDLINE, Scopus. Sources of grey literature that were searched included ProQuest Dissertations and Theses. The eligibility of the studies was independently appraised by a pair of researchers. The findings are delineated through narratives and tabular presentations. RESULTS: The narrative findings are stratified into three primary domains: (1) the theoretical underpinnings of personalized nursing vis-à-vis the integration of blockchain technology; (2) delineation of the specific domains within nursing where blockchain applications are germane to personalized nursing; and (3) the demonstrable impact of blockchain technology on the efficacy of personalized nursing. CONCLUSION: Blockchain technology has wrought profound transformations in the landscape of personalized nursing. As blockchain technology continues to evolve, future scholarship necessitates elucidation on the conceptual intricacies of personalized nursing interfaced with blockchain technology, and broadening of the research purview to encompass a comprehensive understanding of the various applications of personalized nursing. REPORTING METHOD: This scoping review adhered to relevant EQUATOR guidelines and used the PRISMA-ScR.
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Blockchain technology has become crucial in improving the privacy and security of enterprise applications in the cyber world. However, scalability has become a significant concern for researchers in large organizations, especially those with complex hierarchies and access privileges. As a result, the existing models and consensus algorithms suffer from various issues. Medical centers and healthcare providers are particularly affected by this problem due to the vast amount of data, making it a critical weakness of traditional database management systems. To address this issue, the authors propose a hierarchical model within the Hyperledger Fabric enterprise application, focusing on the healthcare sector as a use case. This model includes multiple organizations at different levels of the hierarchy, such as hospitals, hospital governance, and insurance companies. The initial implementation of this model includes two levels of hierarchy, demonstrating networks of hospitals joining an insurance company. The primary objective of the experiment is to test and improve the network's performance using this model. The model's performance is evaluated by manipulating and scaling environmental factors such as the number of organizations, transaction numbers, channels, block intervals, and block sizes. The benchmarking tool used for this assessment is Hyperledger Caliper, which measures indicators such as success and failure rates, throughput, and latency. Currently, the research focuses only on testing the model's scalability using patient data.
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Methods: We utilized a 4D framework using ease of implementation, novelty, necessity, and fit of the overall industry to examine the adoption of blockchain technology in the pharmaceutical industry. Based on the 2D framework of difficulty and novelty as driving factors for the development of foundational technologies in the world of business by Iansiti and Lakhani, each application was ranked and scored for the best potential implementation. The potential applications proposed in this paper can be grouped into two main categories. The first category, management, includes best-use cases, such as health records, clinical trials, and inventory systems. The second category, monitoring, highlights cases, such as pharmaceutical products, preventing counterfeits, optimizing supply chains, and addressing prescription misuse and abuse. Results: Each application was ranked by the four metrics in the framework, giving the greatest weight to necessity and ease of implementation. Using the highlighted methodology earlier, the applications for best implementation include Prescription Drug Misuse and Abuse Prevention, Prevention of Counterfeits, Clinical Trial Outcomes, and Smart Contracts. Conclusion: Blockchain technology offers a new and promising solution to the pharmaceutical industry's needs. To promote the most appropriate use, each application of blockchain technology must fit within the framework of necessity, ease of implementation, familiarity amongst stakeholders, and fit of the overall industry. By using the extended framework proposed by Iansiti and Lakhani, we show how blockchain, in all these domains, shows promise to improve pharmaceutical industry performance.
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Remote sensing image is a vital basis for land management decisions. The protection of remote sensing images has seen the application of blockchain's notarization function by many scholars. Yet, research on efficient retrieval of such images on the blockchain remains sparse. Addressing this issue, this paper introduces a blockchain-based spatial index verification method using Hyperledger Fabric. It linearizes the spatial information of remote sensing images via Geohash and integrates it with LSM trees for effective retrieval and verification. The system also incorporates IPFS as an underlying storage unit for Hyperledger Fabric, ensuring the safe storage and transmission of images. The experiments indicate that this method significantly reduces the latency in data retrieval and verification without impacting the write performance of Hyperledger Fabric, enhancing throughput and providing a solid foundation for efficient blockchain-based verification of remote sensing images in land registry systems.
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The transformative potential of blockchain technology in the renewable energy sector is increasingly gaining recognition for its capacity to enhance energy efficiency, enable decentralized trading, and ensure transaction transparency. However, despite its growing importance, there exists a significant knowledge gap in the holistic understanding of its integration and impact within this sector. Addressing this gap, the current study employs a pioneering approach, marking it as the first comprehensive bibliometric analysis in this field. We have systematically examined 390 journal articles from the Web of Science database, covering the period from 2017 through the end of February 2024, to map the current landscape and thematic trajectories of blockchain technology in renewable energy. The findings highlight several critical thematic areas, including blockchain's integration with smart grids, its role in electric vehicle integration, and its application in sustainable urban energy systems. These themes not only illustrate the diverse applications of blockchain but also its substantial potential to revolutionize energy systems. This study not only fills a crucial gap in existing literature but also sets a precedent for future interdisciplinary research in this domain, bridging theoretical insights with practical applications to fully harness the potential of blockchain in the renewable energy sector.
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Currently, with the rapid development of smart home technology, the demand for establishing efficient and sustainable smart home systems in rural areas is increasing. However, in rural environments, the effective management and intelligent control of green energy face many challenges. To address these issues, this work aims to design a smart home system based on blockchain technology to achieve efficient energy management and intelligent control in a green lighting environment in rural areas. The main goals include improving the performance and safety of the system to meet the lighting needs of rural areas and promote sustainable development. The system comprises two primary components: the home gateway and cloud services. These components encompass functions like data monitoring and transmission, cloud storage, and remote control. The work also introduces the structural interaction, user node interaction, and the data security transmission scheme of the smart home system. Ultimately, the system's effectiveness is confirmed through simulation experiments. The results demonstrate that the system achieves the lowest latency when the transaction arrival rate is 40tps and the block size is 10. Additionally, the access control scheme based on the Hyperledger Fabric consortium chain can efficiently handle access requests for smart home resources and meet the practical application requirements within an appropriate range of security parameters. The main research conclusion is that the designed smart home system based on blockchain technology has achieved significant results in improving performance and security. This not only provides reliable lighting solutions for rural areas, but also provides important theoretical and practical guidance for the future development of smart home systems. The direction of future work includes further optimizing system performance, expanding the scope of application, and exploring more advanced blockchain technology applications in the field of smart homes. This will provide more possibilities and innovative directions for the development of future smart home systems.
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The rapidly evolving field of Digital Finance necessitates a new, interdisciplinary approach to doctoral training. This manuscript presents a comprehensive curriculum designed to equip early-stage researchers with the skills and knowledge required to navigate the complexities of modern finance. The curriculum is structured around four pillars: Training through Research and Mandatory Scientific Training, Advanced Scientific Training, Transferable Skills Training, and Training through Secondments. Together, these pillars provide a balanced mix of theoretical knowledge, practical experience, and soft skills. The program also emphasizes international collaboration through conferences and offers online courses for accessibility and sustainability. By addressing key challenges such as data quality, deployment of complex models, trust in AI-supported products, and labor shortages, the program aims to foster innovation and competitiveness in the European Finance industry. The curriculum's alignment with the European Digital Finance Package and integration with leading institutions ensures its relevance and potential for significant impact.
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Internet of Things (IoT) paves the way for the modern smart industrial applications and cities. Trusted Authority acts as a sole control in monitoring and maintaining the communications between the IoT devices and the infrastructure. The communication between the IoT devices happens from one trusted entity of an area to the other by way of generating security certificates. Establishing trust by way of generating security certificates for the IoT devices in a smart city application can be of high cost and expensive. In order to facilitate this, a secure group authentication scheme that creates trust amongst a group of IoT devices owned by several entities has been proposed. The majority of proposed authentication techniques are made for individual device authentication and are also utilized for group authentication; nevertheless, a unique solution for group authentication is the Dickson polynomial based secure group authentication scheme. The secret keys used in our proposed authentication technique are generated using the Dickson polynomial, which enables the group to authenticate without generating an excessive amount of network traffic overhead. IoT devices' group authentication has made use of the Dickson polynomial. Blockchain technology is employed to enable secure, efficient, and fast data transfer among the unique IoT devices of each group deployed at different places. Also, the proposed secure group authentication scheme developed based on Dickson polynomials is resistant to replay, man-in-the-middle, tampering, side channel and signature forgeries, impersonation, and ephemeral key secret leakage attacks. In order to accomplish this, we have implemented a hardware-based physically unclonable function. Implementation has been carried using python language and deployed and tested on Blockchain using Ethereum Goerli's Testnet framework. Performance analysis has been carried out by choosing various benchmarks and found that the proposed framework outperforms its counterparts through various metrics. Different parameters are also utilized to assess the performance of the proposed blockchain framework and shows that it has better performance in terms of computation, communication, storage and latency.
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Inadequate information sharing and difficult information diffusion are the main factors that cause upstream and downstream enterprises to default on supply chain finance. Blockchain technology, which exploits distributed storage and a consensus mechanism, can provide effective solutions to overcome these problems such as information sharing. When blockchain technology is adopted by the enterprises that comprise the supply chain finance business, this technology shows a diffusion trend. As a result, the decision pertaining to the application of novel technologies is affected. Therefore, to investigate the diffusion mechanism pertaining to the blockchain technology that is applied in supply chain finance, the study exploited the idea of a class of SEIR infectious disease models, and built a blockchain model that considers the supply chain financial system. Besides, the study verifies the stability of the model by constructing a Lyapunov function. The results indicate that the basic reproduction number determines the proliferation of the blockchain technology. When the basic reproduction number is less than 1, the proliferation of the blockchain technology that is applied in supply chain finance system would terminate. By contrast, when the basic reproduction number is greater than 1, during the average infection period, the number of non-adopting enterprises that accept the blockchain technology becomes greater than 1, which can maintain a continuous impact on supply chain finance system. Over time, the number of enterprises that accept blockchain technology tends to be stable. Through numerical simulations that consider the influencing parameters pertaining to the basic regeneration number, which has important effect on blockchain technology diffusion, we enlarge the diffusion efficiency and increase the transfer rate of potential on-chain enterprises or decrease the default exit rate. As a result, we facilitate the diffusion of blockchain technology in the system.
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BACKGROUND: The pharma supply chain comprises various parties including distributors, manufacturers, raw material suppliers, regulators, pharmacies, hospitals, and patients. Due to the product's complexity and transaction flows, an efficient traceability system is needed in the pharma supply chain to identify the current and all previous product owners. Digitizing the track and trace process significantly improves regulatory oversight and guarantees product quality. A distributed platform for shared data that is immutable, trustworthy, accountable, and transparent in the pharmaceutical supply chain could be built using blockchain-based drug traceability. OBJECTIVE: This review aims to shed light on blockchain technology's significance and necessity for pharmaceutical supply chain management systems. METHOD: A comprehensive literature review was performed between January 2017 and September 2023. The search was conducted to elaborate on blockchain technology. Blockchain is a software-based technology that logs and records transactions using a block structure arranged chronologically. Cryptography technology links and secures these blocks on a peer-to-peer network. Blockchain is anticipated to transform the pharmaceutical supply chain by giving all participants access to a single, straightforward system that provides transparency, security, and oversight of the end-to-end delivery of goods. RESULT: In all, various literature data were included in this review. Using a supply chain powered by blockchain has many benefits. To begin with, it gives a thorough account of the entire procedure from start to finish. A single piece of software can manage the entire supply chain. Additionally, it increases communication between parties with permission. The enhanced security and traceability that blockchain offers is another important benefit. A blockchain system can track, trace, and recall products. CONCLUSION: Blockchain-based pharmaceutical supply chain management enables the tracking of medicinal drug transactions from raw materials suppliers to end consumers. The pharma blockchain has the potential to enhance the security, integrity, data provenance, and functionality of the supply chain due to its transparency, immutability, and auditability.
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Blockchain , Humans , Pharmaceutical Preparations/supply & distribution , Drug Industry/organization & administration , SoftwareABSTRACT
Enterprises across the globe are facing increasing pressure to effectively utilize resources and reduce costs through green supply chain practices. Emerging technology, such as blockchain technology which enables green practices, has become a contemporary industrial paradigm. However, enterprises need to build green intellectual capital to implement blockchain technology, which can be key to realizing green supply chain practices. This research examines the impact of green intellectual capital (GIC) on blockchain technology and its role in implementing green manufacturing to achieve sustainability. Partial least squares structural equation modeling was utilized for assessing the proposed hypotheses, and cross-sectional data was accumulated from manufacturing firms. As per the results, GIC, which includes green human capital, green structural capital, and green relational capital has a crucial role in the implementation of blockchain technology. The outcomes also indicated that the adoption of blockchain technology significantly influences green manufacturing. Moreover, green manufacturing (GM) has a substantial role in improving business sustainability. This empirical research provides a deeper understanding of how GIC and blockchain technology contribute to the implementation of GM. This research also provides guidelines that managers, policymakers, and producers can use to facilitate the incorporation of GM practice into business activities.
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Blockchain , Humans , Cross-Sectional Studies , Commerce , Industry , TechnologyABSTRACT
An overview of blockchain fundamentals and its potential benefits for sustainability is provided. The role of expertise as an intermediary on the blockchain to drive transparency and accountability is examined. This research examines the potential of blockchain technology in the field of economic management and to drive future sustainable development in emerging companies, which are referred to as hidden champions. This study addresses the need for transparent and responsive practices that promote social stability, economic growth, and environmental sustainability. The goals are to analyze economic functions, investigate the formation of appropriate economic patterns, facilitate equitable distribution, and support environmental protection efforts. The research method includes case studies and theoretical frameworks to collect relevant data. The results emphasize the importance of balancing competing interests, promoting security, and strengthening inclusive decision-making processes. This study emphasizes the intersection between economic development and environmental protection and highlights the role of sustainability criteria in guiding land use practices. The conclusion emphasizes that sustainable economic practices are critical for social, economic and environmental development, especially in emerging economies. Practical recommendations are provided to policymakers and stakeholders to improve economic governance frameworks and help achieve the Sustainable Development Goals.
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Ambient Intelligence is a concept that relates to a new paradigm of pervasive computing and has the objective of automating responses from the system to humans without any human intervention. In social media forensics, gathering, analyzing, storing, and validating relevant evidence for investigation in a heterogeneous environment is still questionable. There is no hierarchy for automation, even though standardization and secure processes from data collection to validation have not yet been discussed. This poses serious issues for the current investigation procedures and future evidence chain of custody management. This paper contributes threefold. First, it proposes a framework using a blockchain network with a dual chain of data transmission for privacy protection, such as on-chain and off-chain. Second, a protocol is designed to detect and separate local and global cyber threats and undermine multiple federated principles to personalize search space broadly. Third, this study manages personalized updates by means of optimizing backtracking parameters and automating replacements, which directly affects the reduction of negative influence on the social networking environment in terms of imbalanced and distributed data issues. This proposed framework enhances stability in digital investigation. In addition, the simulation uses an extensive social media dataset in different cyberspaces with a variety of cyber threats to investigate. The proposed work outperformed as compared to traditional single-level personalized search and other state-of-the-art schemes.
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Water is important for every organism, especially human survival. 2-3 % of fresh water is available on the earth's surface. Discharge of contaminated municipal sewage, removal of degradable wastes and industrial effluents has polluted freshwater resources like an ocean, river, pond, channel, or lake. Hence, this precious resource must be carefully maintained and preserved before consumption. In this research, machine learning models such as Linear Regression, Generalized Linear Model, Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), classification and regression trees, and Random Forest were used to predict the water quality parameter of Chittar Pattanam Channel, Kanyakumari district, Tamil Nadu in India by giving latitude and longitude. The results showed that the Random Forest (RF) algorithm was better than other models in terms of prediction accuracy with a mean absolute error of 0.56, mean square error of 0.33, and root mean square error of 0.56. Blockchain technologies were used to provide security in the machine learning model. In this work, more than one authorized person is involved in the prediction process, and the authorized person is verified by his signature using Secure Hash Algorithm-256 (SHA). To generate an unpredictable and unique key, SHA-2 uses the size of hash values is 256,384 and 512, a message size is 1024, total rounds are 80 and a word size is 64bits. RSA (Rivest-Shamir-Adleman) technique is used for performing data transfer of keys and encrypting and decrypting data. This study implements a secure water quality prediction system to reduce pollution and improve water quality.
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Blockchain , Water Quality , Humans , India , Algorithms , Machine Learning , Support Vector MachineABSTRACT
Blockchain technology integrates a series of complex technologies such as distributed accounting,peer-to-peer transmission,cryptography,smart contracts,consensus algorithms,etc.,providing services for controlling,storing,sharing,and managing data.At present,clinical nursing data is growing exponentially,and blockchain technology can be well used to process a large amount of clinical nursing data,bringing many advantages to clinical nursing.This article provides an overview of the current research status of blockchain technology in clinical nursing,with a focus on application types,advantages,and difficulties and challenges in the application process.It also proposes suggestions for designing data models and formats that meet specifications and standards,providing decision support for the application and development of blockchain technology in clinical nursing in China,thereby improving the quality of nursing services.