This study investigates cryptocurrency knowledge, risk perception, and investment strategies among İstanbul Provincial Health Directorate employees. Analyzing data from 399 participants using the Cryptocurrency investment Trust Scale, which is developed by Ozyesil and Tembelo (2023), results indicate limited cryptocurrency awareness, moderate risk perception, and conservative investment tendencies. While most participants have heard of cryptocurrency, their understanding remains shalloyv, perceiving it as high-risk and favoring traditional financial instruments. The study emphasizes the necessity of educational initiatives and regulatory frameworks to facilitate safe and compliant cryptocurrency usage within the healthcare sector.
ChainScience 2024, the second edition of the interdisciplinary conference, brought together academics, practitioners, and industry experts to explore novel developments in the realm of distributed ledger technologies. The conference aimed to bridge diverse fields such as informatics, business, economics, finance, regulation, law, mathematics, physics, and complexity science. The papers presented in these conference proceedings address emerging topics such as AI/ML applications to blockchain, DLTs interoperability, decentralized financial services, and tokenomics, alongside ethical, societal, and governance aspects of blockchain and DLTs. With a focus on promoting high-quality research and interdisciplinary collaboration, ChainScience24 aimed to unlock the collective potential of its diverse participants, embodying the ethos that the whole is greater than the sum of its parts.
Poonam Rani, Akhtar Hussain, Md. Kaiyum Shaikh, M. Suresh Babu
Research on blockchain technology explores the multifaceted aspects of decentralized and distributed ledger systems. Originating with Bitcoin in 2009, the technology has since evolved beyond cryptocurrencies, gaining prominence in diverse sectors such as finance, supply chain, and healthcare. Scholars have investigated the underlying principles, design considerations, scalability challenges, and potential applications of blockchains. This study aims to map blockchain technology research using bibliometrics and a visualization approach. Scholarly publications on blockchain technology were analyzed using quantitative and qualitative indicators from the Web of Science (WoS) database. A total of 5,249 research articles, spanning a decade (2011-2020) were extracted from the WoS database. This analysis has been enriched using various bibliometric tools, including Biblioshiny, VOSviewer, RStudio, and BibExcel. The key findings of this study revealed that the highest annual growth rate of publications occurred in 2018, with 581 records (184.80%). Author Zhang Y published most of the papers (57) with 1,857 citations. China emerged as the most cited country, with 14,779 world citation shares.
Mallellu Sai Prashanth, V. Uma Maheswari, Rajinikanth Aluvalu, M V V Prasad Kantipudi
INTRODUCTION: Blockchain technology is being investigated as a viable solution due to the industry's growing requirement for accountability and traceability. This study describes a fresh method for tracking down medical products that makes use of a decentralised smart contract network set up on the Ethereum blockchain. In order to enable secure and auditable tracking of health products throughout their lifecycle, the suggested system, named "HealthProductTraceability," makes use of the transparency and immutability of blockchain. OBJECTIVES: The system uses a "Product" struct to hold pertinent data such the product name, batch number, temperature, producer, and distributors. To quickly get product information depending on the batch number, a mapping is used. The use of tools to manufacture items, send them to distributors, and market them is one significant contribution of this research.By demanding validation tests, such as verifying that batch numbers are unique and exist before carrying out certain activities, these functions protect the integrity of the traceability system. METHODS: In order to enable interested parties to track the product's travel and temperature changes, the system additionally emits events for product manufacture, distribution, and temperature adjustments. The suggested system is innovative because it can track the temperature of health items from beginning to end on a decentralised, open platform. RESULTS: By utilising blockchain technology, the system lessens reliance on centralised authorities, fosters stakeholder trust, and minimises the likelihood of fraud, forgery, and tampering in the supply chain for health products. The contract's architecture recognises some of the issues with blockchain technology, including scalability and privacy. By investigating solutions like sidechains, off-chain transactions, and enhancements to consensus methods, scalability issues are solved. CONCLUSION: In summary, the suggested HealthProductTraceability system offers a creative and practical solution to the traceability issues facing the health product sector. The solution provides improved transparency, security, and accountability by utilising blockchain technology, paving the path for a more dependable and trustworthy health product supply chain. To increase the system's usefulness and adoption in real-world circumstances, further research can investigate scalability and privacy issues.
Suelen Bianca de Oliveira Sales, Luciana de Paula Soares
O artigo desenvolve a importância e os desafios enfrentados pela propriedade intelectual no âmbito da nova tecnologia non-fungible token. Conhecido em português como token não fungível, promete revolucionar a forma de se relacionar com a arte a partir de unidades de dados únicas e não fungíveis de itens digitais como imagens, músicas ou vídeos, ou seja, trata-se de algo que é dotado de uma certa “unicidade”. O NFT é criado em Blockchain (tecnologia oriunda da criptomoeda Bitcoin), que garante a transparência e a imutabilidade do ativo digital. Por meio de plataformas próprias focadas em registro de jogos e obras de arte, as pessoas têm a possibilidade de registrar suas criações e comercializá-las dentro destes marketplaces, onde já aconteceram leilões milionários. Promete, ainda, revolucionar a aquisição de bens digitais pela internet e transformar o modo de trabalhar das empresas atualmente. Assim, o trabalho discorre sobre as diversas formas, peculiaridades e aplicabilidades dessa inovação, com foco na segurança jurídica à luz da regulamentação da propriedade intelectual.
Traditional cloud-centric approaches are facing increasing demands for instant data processing and significant challenges in meeting the latency requirements of modern applications. Edge computing emerges as a promising approach that brings computation and data storage closer to the edge of the network, enabling real-time decision-making with reduced latency and enhanced efficiency. The paper provides a comprehensive overview of edge computing, describing its fundamental principles, architectural components, and key advantages over centralized cloud infrastructures. By minimizing data transfer latency, edge computing ensures that critical data analysis and processing occur close to data sources, resulting in enhanced responsiveness and improved user experiences. The paper analyzes two case studies, including autonomous driving vehicles and finance, in order to highlight the applications of edge computing in areas where real-time decision-making is crucial. In addition to discussing the benefits of edge computing, the paper addresses the potential challenges and constraints associated with edge computing implementation. Security and privacy concerns in decentralized edge environments are explored, and several protection strategies are described. Finally, the paper outlines the future of edge computing for organizations and the technology industry. In doing so, the paper discusses the potential of edge computing in supporting emerging technologies, such as 5G networks and autonomous systems. Received: December 19, 2023Accepted: February 2, 2024
Wang Jun, Muhammad Shahid Iqbal, Rashid Abbasi, Marwan Omar · 5 authors
Machine learning is playing an increasingly important role in education. This article examines its potential to bring about transformative change in this field. By using machine learning algorithms, physical education teachers can gather and analyze data on student performance and behavior. This enables them to create personalized learning experiences that cater to the unique needs of each student. Machine learning can also track and assess student progress, providing educators with valuable insights into the effectiveness of their teaching strategies. Furthermore, it can optimize the design of physical education curricula and assessments, making them more efficient and effective. Additionally, machine learning offers a more objective and accurate approach to evaluating and grading students. This paper discusses the challenges and opportunities associated with integrating machine learning into physical education, including ethical considerations and potential limitations.
Mifta Ahmed Umer, Elefelious Getachew Belay, Luís Borges Gouveia
Cloud manufacturing is an evolving networked framework that enables multiple manufacturers to collaborate in providing a range of services, including design, development, production, and post-sales support. The framework operates on an integrated platform encompassing a range of Industry 4.0 technologies, such as Industrial Internet of Things (IIoT) devices, cloud computing, Internet communication, big data analytics, artificial intelligence, and blockchains. The connectivity of industrial equipment and robots to the Internet opens cloud manufacturing to the massive attack risk of cybersecurity and cyber crime threats caused by external and internal attackers. The impacts can be severe because the physical infrastructure of industries is at stake. One potential method to deter such attacks involves utilizing blockchain and artificial intelligence to track the provenance of IIoT devices. This research explores a practical approach to achieve this by gathering provenance data associated with operational constraints defined in smart contracts and identifying deviations from these constraints through predictive auditing using artificial intelligence. A software architecture comprising IIoT communications to machine learning for comparing the latest data with predictive auditing outcomes and logging appropriate risks was designed, developed, and tested. The state changes in the smart ledger of smart contracts were linked with the risks so that the blockchain peers can detect high deviations and take actions in a timely manner. The research defined the constraints related to physical boundaries and weightlifting limits allocated to three forklifts and showcased the mechanisms of detecting risks of breaking these constraints with the help of artificial intelligence. It also demonstrated state change rejections by blockchains at medium and high-risk levels. This study followed software development in Java 8 using JDK 8, CORDA blockchain framework, and Weka package for random forest machine learning. As a result of this, the model, along with its design and implementation, has the potential to enhance efficiency and productivity, foster greater trust and transparency in the manufacturing process, boost risk management, strengthen cybersecurity, and advance sustainability efforts.
Alven C. Y. Leung, Dennis Liu, Xiapu Luo, Man Ho Au
Abstract Blockchain is a newly emerging technology in the past decade that has significantly impacted various aspects. “Scientific popularization” among IT practitioners on this technology and its use cases become a pressing need. However, constructing an effective blockchain teaching approach for this purpose is a challenging task. A training framework consisting of constructivist and pragmatic approaches is proposed, aiming to provide IT practitioners with an effective Teaching and Learning (T &L) process about blockchain on both theory and application aspects. The outcomes of this study are to 1) propose an effective teaching methodology, 2) assess the effectiveness of constructivist and pragmatic approaches and 3) extract the elements facilitating blockchain T &L. Mixed quantitative and qualitative research methods were adopted, including questionnaires and knowledge quizzes. 1267 participants were involved in the training that implemented the proposed framework. Their performance and responses indicated that the framework is effective and flexible. The findings from this empirical research can serve as a reference for educators in blockchain to implement a systemic approach that facilitates the T &L process and improves the field of blockchain and education in the future.
In the context of blockchain technology and cryptocurrencies, computer graphics integration seeks to improve data visualization and user interfaces, offering intuitive and aesthetically pleasing experiences. This entails developing immersive user interfaces for decentralized apps, strengthening security using visual cryptography, and increasing accessibility to complicated blockchain data. Visualizations help users comprehend transaction patterns and system efficiency by making blockchain data easier to analyze. The ultimate goal of this strategy is to improve the usability and engagement of interactions with digital assets and blockchain technology. Index Terms: Blockchain technology, cryptocurrency, data visualization, Computer Graphics, Supply chain, finance.
Much of the attention on bitcoin relates to its ability to store value over time or whether you will one day by able to buy a cup of coffee with it. Much less attention is given to bitcoin’s potential role as a unit of account. This opinion piece proposes that bitcoin has potential to provide a consistent unit of account for organisations to adopt, but also to assist them in making and measuring meaningful business developments. The paper draws from the business improvement philosophy of Theory of Constraints to propose that unit of account, particularly within high inflation environments, is critical to consider. An illustrative case of a well-known publicly traded company, Microstrategy, provides an example and logic for a company choosing to integrate bitcoin into a business. The paper also gives attention to how the adoption of bitcoin can promote the development of renewable energy infrastructure and provide staff with opportunities for personal development to support their well-being. Opportunities for further research are identified to explore the integration of bitcoin within a business as well as with Theory of Constraints.
The purpose of the article is a theoretical review of the formation and development of the latest marketing technologies and their practical adaptation to the entrepreneurial activity of Ukrainian business entities. The main marketing technologies developed by different markets and used by business structures of medium-sized businesses are considered. It is detailed that when conducting office research, marketers use Big Data technology as a technology for processing large volumes of structured and unstructured data for their further use in order to solve various tasks. It is specified that effective marketing technologies such as SMM (Social Media Markitang), SEO (Search Engine Optimization), Tableau technologies, Google Data Studio, Microsoft Power BI, TRI*M, digital advertising and CRM technology are in the arsenal of marketers for conducting field research. . The main new marketing technologies are separated, namely: NFT technology (Non-Fungible Tokens), AR/VR (augmented reality/virtual reality) technology and artificial intelligence technology. According to the conducted studies, it was established that CRM technology is currently used by all business structures, digital advertising technology - 95%, SMM technology - 85%, TRI*M and SEO technologies - 75%. It is detailed that artificial intelligence technology is used by large and medium-sized business companies in the following areas: personalized automation, omnichannel, omnichannel marketing, the field of brand community formation and creation of texts, images for its promotion, etc.
In the modern digital landscape of the Internet of Things (IoT), data interoperability and heterogeneity present critical challenges, particularly with the increasing complexity of IoT systems and networks. Addressing these challenges, while ensuring data security and user trust, is pivotal. This paper proposes a novel Semantic IoT Middleware (SIM) for healthcare. The architecture of this middleware comprises the following main processes: data generation, semantic annotation, security encryption, and semantic operations. The data generation module facilitates seamless data and event sourcing, while the Semantic Annotation Component assigns structured vocabulary for uniformity. SIM adopts blockchain technology to provide enhanced data security, and its layered approach ensures robust interoperability and intuitive user-centric operations for IoT systems. The security encryption module offers data protection, and the semantic operations module underpins data processing and integration. A distinctive feature of this middleware is its proficiency in service integration, leveraging semantic descriptions augmented by user feedback. Additionally, SIM integrates artificial intelligence (AI) feedback mechanisms to continuously refine and optimise the middleware’s operational efficiency.
The precise characterization and modeling of Cyber-Physical-Social Systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This letter reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by a range of technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the ``6A-goal" of ACS and propose potential avenues for future research.
Mohammed Alshamsi, Mostafa Al‐Emran, Tuğrul Daim, Mohammed A. Al‐Sharafi · 6 authors
The increasing popularity of Blockchain technology has led to its adoption in various sectors, including higher education. However, the sustainability of Blockchain in higher education is yet to be fully understood. Therefore, this research examines the determinants affecting Blockchain sustainability by developing a theoretical model that integrates the protection motivation theory (PMT) and expectation confirmation model (ECM). Based on 374 valid responses collected from university students, the proposed model is evaluated through a deep learning-based hybrid structural equation modeling (SEM) and artificial neural network (ANN) approach. The PLS-SEM results confirmed most of the hypotheses in the proposed model. The sensitivity analysis outcomes discovered that users' satisfaction is the most important factor affecting Blockchain sustainability, with 100% normalized importance, followed by perceived usefulness (58.8%), perceived severity (12.1%), and response costs (9.2%). The findings of this research provide valuable insights for higher education institutions and other stakeholders looking to sustain the use of Blockchain technology.
Jan 1, 2024·Proceedings of the 4th LACCEI International Multiconference on Entrepreneurship, Innovation and Regional Development (LEIRD 2024): "Creating solutions for a sustainable future: technology-based entrepreneurship"
Blockchain emerges as an innovative technology with potential applications in the healthcare sector due to its demonstrated qualities of decentralization, distribution, and data integrity. This systematic literature review (SLR), without metaanalysis, aims to analyze current perspectives and trends in blockchain interoperability for information systems in the healthcare sector, focusing on challenges and opportunities to enhance healthcare data management through this technology. Using the PICO strategy and PRISMA methodology, 25 openaccess articles from Scopus and PubMed databases were reviewed, addressing blockchain interoperability and healthcare between 2020 and 2024. The results highlight those perspectives on blockchain interoperability in healthcare focus on improving efficiency and security in data exchange through a decentralized network. Furthermore, trends indicate the use of platforms and standards such as FHIR, IPFS, Ethereum, and Hyperledger to facilitate this exchange. In conclusion, this study underscores blockchain's potential to transform health data management and exchange through cryptographic mechanisms that enhance the security and efficiency of information systems. It also identifies trends and the use of these platforms and standards that contribute to achieving interoperability.
The primary objective of this project was to improve the cryptocurrency brokerassessment model for a financial services evaluation platform. This initiative focused onreassessing existing cryptocurrency exchanges in the company’s assessment model bysearching and updating the input data, and, eventually, providing recommendations formodel improvement. Ultimately, the project aimed to improve the accuracy of theplatform's evaluations to assist their users in making informed financial decisions.
Based on Google Trends, searches related to cryptocurrency have significantly increased in the last couple of years. One crucial aid for cryptocurrency traders or investors is the graphical visualization, which shows the time series data of the cryptocurrency prices. However, problems may occur in data visualization, such as visual noise and information loss, which cause perceptual and cognitive errors in data reading. Therefore, good visualization is needed to avoid decision-making mistakes, particularly in the cryptocurrency trade and investment activities. This study aims to investigate the effect of chart design and time interval on the usability of data visualization. The experiments are conducted in two scenarios, i.e., with and without time pressure. The participants recruited in this study were non-experienced and experienced people classified based on their familiarity with cryptocurrency investment/trading. Objective usability testing is performed by eye tracking, while subjective assessment employs the System Usability Scale (SUS) questionnaire. There are four quantitative dependent variables: response time, number of errors, number of fixations, and time to first fixation. The results show that time interval and time pressure significantly affect usability for both groups of respondents. Although chart design does not substantially affect the dependent variables, a candle chart is generally better than a line chart. By comparing all the combinations of chart design and time intervals, this study concluded that combining candle charts with 1-hour or 4-hour time intervals gives the best results for both respondent groups.
Muhammad Imran Sarwar, Imran Khan, Louai A. Maghrabi, Arfan Jaffar · 5 authors
With the emergence of FinTech and evolution in the design and delivery of financial services, the Accounting Information System (AIS) needs to evaluate its underlying accounting methods to establish a reliable bookkeeping environment and stay up to date with technological standards and bookkeeping requirements. Many academic studies and practitioner articles have discussed Triple-Entry Accounting (TEA) and AIS researchers are not new to the idea of TEA, but its practical impact remains limited. Blockchain has emerged in financial applications, and it carries the same concept of distributed ledgers as shared ledgers in TEA. Unlike the traditional Double-Entry Accounting (DEA) system, where two parties record and maintain their books of accounts independently, the TEA model incorporates a third entry to further ensure trust and security. However, the lack of underlying accounting methods for recording the third entry, along with compliance issues and other challenges, has raised concerns with TEA, leading to limited practical implementation. This study bridges the gaps in the existing literature by proposing an alternative to TEA: a blockchain, RDBMS, and DEA-based hybrid Tripartite Accounting Framework (TAF). This integration not only adheres to DEA principles but also introduces a third transaction that meets bookkeeping requirements and addresses the limitations in the existing bookkeeping methods for recording B2B (Business-to-Business) transactions. The proposed framework provides a cost-effective and viable solution and ensures trust and security in the B2B trading environment.