Private Datapods: Web 3.0 does not Automatically Mean Blockchain Decentralization

ICT and blockchain professionals must be careful not to equate Web 3.0 automatically with blockchain, or vice versa. That is an incorrect equivalence. Blockchain is certainly one possible architecture on which to base a Web 3.0 implementation. However, the essence of Sir Tim Berners-Lee’s decentralized Web 3.0 concept is nothing automatically or implicitly to do with blockchain, but, rather, is focused on the important idea of Private Datapods. The author’s own Zykme / ZykPass invention is an available working hybrid App (beta test version) compliant with this Web 3.0 Private Datapod fundamental design principle, ushering-in a new era of decentralized user-controlled and user-owned social media based on secure P2P personal data communications, implemented using edge computing. This article describes the architecture and future development of this invention. This includes potential addition of a future blockchain-based ‘social media’ ZykToken, awarded to, and owned and tradeable by, each Zykme / ZykPass user, implementing the author’s novel CapChere (Customer Corporation) IP and business ownership structure. This contends to be a transformative, socially useful re-purposing of traditional industrial capitalism in which all are winners

Improving Patient Care with Machine Learning: A Game-Changer for Healthcare

Machine learning has revolutionized the field of healthcare by offering tremendous potential to improve patient care across various domains. This research study aimed to explore the impact of machine learning in healthcare and identify key findings in several areas.Machine learning algorithms demonstrated the ability to detect diseases at an early stage and facilitate accurate diagnoses by analyzing extensive medical data, including patient records, lab results, imaging scans, and genetic information. This capability holds the potential to improve patient outcomes and increase survival rates.The study highlighted that machine learning can generate personalized treatment plans by analyzing individual patient data, considering factors such as medical history, genetic information, and treatment outcomes. This personalized approach enhances treatment effectiveness, reduces adverse events, and contributes to improved patient outcomes.Predictive analytics utilizing machine learning techniques showed promise in patient monitoring by leveraging real-time data such as vital signs, physiological information, and electronic health records. By providing early warnings, healthcare providers can proactively intervene, preventing adverse events and enhancing patient safety.Machine learning played a significant role in precision medicine and drug discovery. By analyzing vast biomedical datasets, including genomics, proteomics, and clinical trial information, machine learning algorithms identified novel drug targets, predicted drug efficacy and toxicity, and optimized treatment regimens. This accelerated drug discovery process holds the potential to provide more effective and personalized treatment options.The study also emphasized the value of machine learning in pharmacovigilance and adverse event detection. By analyzing the FDA Adverse Event Reporting System (FAERS) big data, machine learning algorithms uncovered hidden associations between drugs, medical products, and adverse events, aiding in early detection and monitoring of drug-related safety issues. This finding contributes to improved patient safety and reduced occurrences of adverse events.The research demonstrated the remarkable potential of machine learning in medical imaging analysis. Deep learning algorithms trained on large datasets were able to detect abnormalities in various medical images, facilitating faster and more accurate diagnoses. This technology reduces human error and ultimately leads to improved patient outcomes.While machine learning offers immense benefits, ethical considerations such as patient privacy, algorithm bias, and transparency must be addressed for responsible implementation. Healthcare professionals should remain central to decision-making processes, utilizing machine learning as a tool to enhance their expertise rather than replace it. This study showcases the transformative potential of machine learning in revolutionizing healthcare and improving patient care

Panel on Privacy in the Hyperconnected Digital Age

This panel is organized to discuss what is needed to gain a comprehensive understanding of the emerging privacy issues thrust upon by modern technologies, such as AI, and the data collection and usage practices of the companies and the government. The panel will explore possible solutions to ensure that these technologies\u27 benefits outweigh their disadvantages. The panel will be held virtually

Metaverse in the tourism domain – introduction to the special issue

In times of technological innovation and digital transformation, the convergence of Metaverse and tourism emerges as a compelling and revolutionary intersection. As we stand on the edge of a new frontier in information technology, we introduce this special issue of the Journal of Information Technology and Tourism, dedicated to the multifaceted exploration of the Metaverse’s impact on the tourism industry. The Metaverse comprises interconnected digital spaces where users can engage through computer-generated environments. This convergence of cutting-edge tech- nologies, including artificial Intelligence (AI) systems, digital twins, augmented reality (AR), virtual reality (VR), blockchain, non-fungible tokens (NFTs), 3D mod- elling and simulation, cloud computing, and edge computing, defines the Metaverse’s potential. The Metaverse’s profound Influence on the tourism domain is well attested by the rigorous examinations, insightful analyses, and innovative research contributions in this issue. As we embark on this exploration, we encourage researchers, scholars, and industry experts to contribute their expertise and insights, forging a path toward a deeper understanding of the Metaverse’s implications for the future of tourism

Analysis of New Advances in the Application of Artificial Intelligence to Education

Artificial intelligence is an important innovation in the rapid development of modern Internet. In the 21st century, human beings have been continuously researching and exploring Internet information technology. All kinds of application forms of Internet informatization begin to appear in our life. The rapid change of technology brings a high upgrade rate of internet products. This marks the technological innovation of some traditional concepts and thinking methods. The development mode of artificial intelligence plus education is an important innovation after the deep development of artificial intelligence technology and the achievement of cross-industry application practice. Robots will be the brains of the future education process. This paper aims to clarify the development trend of the application of artificial intelligence in modern education by analyzing the innovation progress of the combination of artificial intelligence technology and contemporary education. This is of great significance for better use of the advantages of artificial intelligence to build a future-oriented high-tech education system

Membrane traffic in the post-genomic era

A multi-parametric genetic screening approach sheds light on integrated control of the endocytic pathway in mammalian cells

New advances in the application of AI to education system

Artificial intelligence is an important innovation in the rapid development of modern Internet. In the 21st century, human beings have been continuously researching and exploring Internet information technology. All kinds of application forms of Internet informatization begin to appear in our life. The rapid change of technology brings a high upgrade rate of internet products. This marks the technological innovation of some traditional concepts and thinking methods. The development mode of artificial intelligence plus education is an important innovation after the deep development of artificial intelligence technology and the achievement of cross-industry application practice. Robots will be the brains of the future education process. This paper aims to clarify the development trend of the application of artificial intelligence in modern education by analyzing the innovation progress of the combination of artificial intelligence technology and contemporary education. This is of great significance for better use of the advantages of artificial intelligence to build a future-oriented high-tech education system. (DIPF/Orig.