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.
Yung Po Tsang, Youqing Fan, C.K.M. Lee, H.C.W. Lau
In today’s competitive and volatile e-commerce markets, effective supply chain performance measurement (SCPM) gradually becomes essential for investigating pitfalls and loopholes in strategic vendor management and business development. Surrounding the atmosphere of Industry 5.0, sustainability and resilience are two primary pillars, which should be further considered in the SCPM beyond merely operational effectiveness and efficiency. This study customises evaluation criteria based on the green supply chain operations reference model. Moreover, a blockchain sharding-enabled performance analytics system is designed, where a real-life case analysis is conducted to verify the system efficacy. Consequently, the supply chain sustainability and resilience can be fostered.
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.
Sumit Oberoi, Sugandh Arora, Balraj Verma, Krishna Kanta Roy
This study aims to identify artificial intelligence and blockchain technology's publication productivity and intellectual structure in the healthcare industry. This study employs a bibliometric-content analysis technique to determine intellectual structure and publication productivity. The Scopus database analyses identified research articles from 2018 to 2023. The findings of the thematic mapping show that AI and blockchain are emerging techniques and topics such as “smart healthcare”, “patient-centric”, “healthcare management”, “virtual & augmented reality”, “decentralization”, etc. are the potential and new dimensions that can be looked upon in future themes. This study advances knowledge by providing a current and future overview of AI and blockchain integration in the healthcare industry that would create new and enhance existing research streams.
Artificial Intelligence in Healthcare and Education
A. Darwiesh, M. Elhoseny, A. H. El-Baz, Mohamed A. Nour
This study presents a new approach to predict cryptocurrencies risks based on social media platform indicators. This method can help cryptocurrency investors in their future decision-making. It utilizes advanced techniques such machine learning and natural language processing. Furthermore, a case study on American cryptocurrency investors is provided to help them identify and assess the risks associated with their purchases. Moreover, performance metrics are computed to demonstrate the capabilities of the new approach.
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.
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 perspective reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by foundation intelligence and its associated 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.
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.
This chapter compares how blockchain, the Internet of Things (IoT), and artificial intelligence (AI) technologies are used in supply chain to promote sustainability. The chapter starts with explaining the concept of supply chains and their increasing importance in today’s business world. It explores the challenges and objectives involved in managing supply chains, which sets the foundation for examining how blockchain, IoT and AI contribute to this transformative approach. The study extensively analyses how blockchain advances the sustainability of supply chains. It provides insights into real-world implementations and evaluates their social impacts. Additionally, it explores applications of IoT that utilize sensor technology for monitoring conditions, tracking assets, and reducing waste within supply chains. The study also investigates how AI contributes to sustainability through activities like demand forecasting, optimization, resource management, predictive maintenance, and energy conservation. This research highlights the potential of blockchain, IoT, and AI in advancing supply chain management. It offers a nuanced understanding of these technologies’ strengths and weaknesses plus their cost effectiveness and adaptability in supply chain. It draws on real life examples from organizations that have successfully utilized these technologies to improve integration opportunities and overcome challenges. This research contributes to the understanding of the critical role played by blockchain, IoT, and AI technologies for the achievement of sustainability goals within supply chains. It offers practical recommendations for researchers, policymakers, and supply chain practitioners, enabling them to optimize the use of technologies in achieving sustainable supply chains. In conclusion, this study predicts the trends in integration of technology for supply chain sustainability.
The dramatic development of technology in recent years has affected most organizations and companies. Artificial intelligence (AI) and Blockchain can be mentioned as the most important technologies that are developing rapidly. In Industry 4.0, complex data are produced in high volume, which makes implementing improvement projects with traditional methods lose their effectiveness. Six Sigma is one of the most prominent improvement methods organizations and companies use to identify and solve problems. Therefore, for implementing Six Sigma projects in Industry 4.0, the need to develop the traditional Six Sigma toolbox is felt. AI and Blockchain can be suitable tools for developing and improving Six Sigma for Industry 4.0. A systematic review identified 58 articles in this article that presented solutions for integrating AI or Blockchain in Six Sigma. Some articles have evaluated the performance of their proposed method by implementing the proposed models. The most widely used machine learning and deep learning algorithms in Six Sigma have been identified. Also, Six Sigma approaches that mostly use AI or Blockchain have been identified by the analysis of articles. Decision tree algorithms and artificial neural networks are used in most Six Sigma define–measure–analyze–improve–control (DMAIC) projects. Therefore, by reviewing the articles, it was found that AI and Blockchain are mainly used as efficient tools in DMAIC and the Design for Six Sigma models to implement Six Sigma projects. In this article, 28 main gaps are presented as future works for future research.
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.
Blockchain technology and BPMN (Business Process Model and Notation) hold great promise for revolutionizing a wide range of industries by improving transparency, security, and efficiency. In this paper, we propose an integration model for the systematic translation of any BPMN process into a Blockchain with smart contracts. Essentially, our approach aims to support smart contract practitioners working on complex business cases or those new to Solidity by simplifying the language and providing a clear, user-friendly path to translate business processes into effective Solidity code. Our model was applied in a real-world case study to streamline multiple-choice question (MCQ) creation and management in education. Finally, this paper discusses the potential impact of this integrated approach on educational assessment practices and suggests avenues for future research and development.
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.