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Research Article
The Revolutionary Impact of AI, Machine Learning, Web3.0, Blockchain, Metaverse and NFTs on Global Society in the Next Decade
Ali Mansoor Pasha*
Issue:
Volume 8, Issue 3, September 2025
Pages:
138-144
Received:
21 July 2025
Accepted:
4 August 2025
Published:
19 August 2025
Abstract: This article explores how the integration of Artificial Intelligence (AI), Machine Learning (ML), Web3.0, Blockchain, Metaverse, and Non-Fungible Tokens (NFTs) will revolutionize various aspects of public life globally over the next decade. We introduce novel perspectives such as AI-driven decentralized governance, blockchain-based universal basic income, and metaverse-enabled global education platforms. These technologies will transform global supply chains through AI-driven forecasting and blockchain-verified logistics, ensuring transparency and efficiency. Healthcare will advance with AI-powered telemedicine and personalized treatments, reducing disparities in underserved regions. Autonomous systems will enhance urban mobility and disaster response, fostering sustainable smart cities. Web3.0 will empower users with decentralized digital identities and data sovereignty, redefining advertising and social media through token-based models. Blockchain will secure academic credentials, streamline insurance, and enable transparent philanthropy, while carbon credit markets promote sustainability. The metaverse will revolutionize remote work, healthcare consultations, and cultural preservation through immersive virtual environments. NFTs will democratize real estate and creative economies, enabling tokenized ownership and secure voting systems. Synergistically, these technologies will create decentralized e-commerce, disaster response systems, and virtual innovation hubs, fostering equitable digital ecosystems. However, challenges like digital divides, AI biases, and blockchain scalability must be addressed to ensure inclusive adoption. This article envisions a future where these advancements redefine governance, economies, and social interactions, paving the way for an innovative, equitable global society. AI-driven avatars and decentralized AI training platforms will further enhance virtual collaboration, while tokenized cultural assets empower communities, ensuring a resilient, inclusive digital future.
Abstract: This article explores how the integration of Artificial Intelligence (AI), Machine Learning (ML), Web3.0, Blockchain, Metaverse, and Non-Fungible Tokens (NFTs) will revolutionize various aspects of public life globally over the next decade. We introduce novel perspectives such as AI-driven decentralized governance, blockchain-based universal basic ...
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Research Article
Practical Exercises for Learning the APA Standard 7th Edition from the Subject Management of Computerization
Issue:
Volume 8, Issue 3, September 2025
Pages:
145-150
Received:
4 May 2025
Accepted:
7 June 2025
Published:
8 September 2025
Abstract: The rapid evolution of Information and Communication Technologies (ICT) has generated changes in almost all aspects of society, and higher education is no exception, as traditional teaching methodologies have had to be transformed. Despite this, challenges persist in higher education regarding specific skills, such as proper citation of the APA 7th edition, which is crucial for academic integrity. Previous studies have found that traditional approaches show limitations in retention and practical transfer, specifically among first-year students. The objective was to design practical exercises to facilitate learning of the APA 7th edition among first-year students in the Agroindustrial Process Engineering program. The materials included interactive guides, the use of APA format templates, and digital tools that were integrated into real-life program projects. The results indicate that 92% of students managed to improve their citation and referencing accuracy, increasing the retention of technical standards by 40% compared to conventional methods. In conclusion, it can be stated that the use of ICT not only improves the technical understanding of the APA standard but also develops critical skills for professional academic production. This proposal proves scalable to other disciplines, highlighting the need to integrate digital tools into the teaching of methodological skills.
Abstract: The rapid evolution of Information and Communication Technologies (ICT) has generated changes in almost all aspects of society, and higher education is no exception, as traditional teaching methodologies have had to be transformed. Despite this, challenges persist in higher education regarding specific skills, such as proper citation of the APA 7th...
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Review Article
Cybersecurity Vulnerabilities and Intrusion Detection Mechanisms in Wireless Sensor Networks: A Review
Issue:
Volume 8, Issue 3, September 2025
Pages:
151-163
Received:
8 August 2025
Accepted:
21 August 2025
Published:
19 September 2025
Abstract: Wireless Sensor Networks (WSNs) have become integral to various sensitive and life-critical areas and applications, including environmental monitoring, healthcare, and smart cities. However, their widespread adoption raises significant cybersecurity concerns due to inherent vulnerabilities in their architecture, communication protocols, and resource constraints. This paper comprehensively analyzes security vulnerabilities specific to WSNs. Physical vulnerabilities arise from the unattended deployment of sensor nodes, making them susceptible to tampering and theft. Network-layer vulnerabilities include issues such as eavesdropping, replay attacks, and denial of service, which can severely disrupt the functionality of WSNs. Application-layer vulnerabilities often involve inadequate security measures in software, leading to data breaches and manipulation. In the face of these threats, traditional threat detection mechanisms are deficient in addressing the problem due to the inherent properties of the sensor nodes, such as limited energy, processing power, and memory. This led to the development of custom Intrusion Detection Systems (IDS) for WSNs. IDS can be classified into various types based on detection method, architecture, and deployment strategy. Additionally, this paper evaluates existing intrusion detection mechanisms designed to mitigate these vulnerabilities. We categorize these mechanisms into anomaly-based and signature-based approaches, analyzing their strengths and limitations concerning WSNs’ unique characteristics. Anomaly-based systems are adept at detecting novel attacks but may suffer from high false-positive rates, while signature-based systems offer faster detection for known threats but struggle with the emergence of new vulnerabilities. We also highlight recent advancements in machine learning and artificial intelligence as innovative approaches for enhancing intrusion detection capabilities in WSNs. These strategies promise to improve the accuracy and efficiency of intrusion detection systems by leveraging large datasets to recognize complex attack patterns. Based on our findings, this article underscores the urgent need for robust security frameworks tailored to WSN environments. This review work is aimed at providing researchers and practitioners with foundational information to aid their understanding of the security posture of wireless sensor networks.
Abstract: Wireless Sensor Networks (WSNs) have become integral to various sensitive and life-critical areas and applications, including environmental monitoring, healthcare, and smart cities. However, their widespread adoption raises significant cybersecurity concerns due to inherent vulnerabilities in their architecture, communication protocols, and resourc...
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Research Article
Bridging Mind and Machine: Large Language Models in Next Generation Brain Computer Interfaces
Issue:
Volume 8, Issue 3, September 2025
Pages:
164-173
Received:
25 August 2025
Accepted:
3 September 2025
Published:
25 September 2025
Abstract: Brain Computer Interfaces (BCIs) have advanced from experimental research to translational applications in communication, rehabilitation, and human machine interaction. Yet, BCIs face fundamental challenges like decoding high-dimensional, noisy neural data, producing fluent outputs, adapting to individual users, and scaling to real-world environments. Large Language Models (LLMs) represent a transformative capability that can directly mitigate these challenges. By leveraging their strengths in probabilistic reasoning, context completion, error correction, and multimodal integration, LLMs have the potential to unlock new levels of efficiency, personalization, and accessibility in BCI systems. This paper examines the convergence of LLMs and BCIs. It outlines the technical landscape, opportunities, case studies, and open questions, with a focus on communication BCIs, adaptive rehabilitation, and cognitive modeling. Brain-Computer Interfaces (BCIs) are rapidly transforming the way we understand and interact with technology. Once the stuff of science fiction, these innovative systems now bridge the gap between the human brain and digital devices, allowing thought to shape action in unprecedented ways. As artificial intelligence (AI) continues to evolve, particularly with the rise of Large Language Models (LLMs) and Agentic AI platforms, the partnership between BCIs and these advanced technologies is opening doors to a new era of intelligent, personalized, and intuitive machines.
Abstract: Brain Computer Interfaces (BCIs) have advanced from experimental research to translational applications in communication, rehabilitation, and human machine interaction. Yet, BCIs face fundamental challenges like decoding high-dimensional, noisy neural data, producing fluent outputs, adapting to individual users, and scaling to real-world environmen...
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