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- Tài liệuAdvancements in Natural Language Processing, Semantic Networks, and Sentiment Analysis(MDPI, 2025) García-Méndez, Silvia; Costa-Montenegro, Enrique; Arriba-Pérez, Francisco DeThis Special Issue examines the intersection of NLP, semantic networks, and sentiment analysis, exploring how these technologies can contribute to more intelligent systems. The contributions gathered address, among other topics, the detection of irony and sarcasm, the generation of semantic explanations, the automatic construction of semantic graphs, the expansion of linguistic resources for underrepresented languages, and the use of large language models. Ultimately, this Special Issue aims not only to reflect the state of the art in the areas above but also to stimulate critical reflection on the methodological challenges, ethical implications, and interdisciplinary opportunities that arise at the intersection of computational linguistics and artificial intelligence.
- Tài liệuIoT Security: Threat Detection, Analysis and Defense(MDPI, 2025) Markowitch, Olivier; Dricot, Jean-MichelInternet of Things technologies, which connect various devices and sensors together, are increasingly at the basis of modern communication, enabling the autonomous exchange of data between billions of physical and virtual objects, creating smart environments in sectors such as healthcare, logistics, etc. However, the advancement of IoT communication also brings new security challenges. Managing the security of the IoT raises major concerns, especially when devices are deeply integrated into critical infrastructure, hospitals, and vehicles. Furthermore, the IoT is a key component of 5G/6G architecture and Industry 4.0. All these technologies are designed to support critical applications. The increased number of related potential attack vectors poses a substantial risk for malicious attackers. Also, the focus of security has been put on large-scale, software-oriented systems, such as the Cloud or datacenter systems, rather than embedded electronics. Consequently, the establishment of IoT ecosystems across different domains remains highly vulnerable to a wide range of threats. This Special Issue gathers high-quality original research contributions and the latest research results in the field of threat detection within the IoT. It also covers threat analysis and corresponding defense techniques. The threats are related to privacy issues, trust issues, IoT management issues, IoT intrusion, vulnerability issues, malware detection, cryptographic key management, reliability of IoT communication (including secure routing aspects), IoT forensics techniques, Cloud-related IoT issues, etc.
- Tài liệuSensors for Physiological Monitoring and Digital Health(MDPI, 2025) Naik, Ganesh R.; Pirogova, Elena; Lech, MargaretThe Special Issue, “Sensors for Physiological Monitoring and Digital Health”, successfully bridged different scientific disciplines, providing a platform for highly innovative research. The issue showcased the significant potential of health monitoring through physiological signals for personalized healthcare. It highlighted the need for long-term monitoring in both clinical settings, to aid in diagnosis, treatment, and ongoing patient care, and in home settings, to offer continuous remote monitoring, potentially improving health outcomes and reducing healthcare costs. Reliable monitoring of vital parameters like EEG, EMG, and heart rate for elderly and chronic patients, a challenge effectively met by developing continuous, real-time, and nonintrusive wearable, highly integrated sensor networks. The issue captured the rapid growth of the wearable medical device market and the evolution of biosensors and textile-based technologies, driven by advancements in microfabrication, flexible electronics, nanomaterials, and advances in wireless communication. It also explored how physiological monitoring using AI-powered digital health platforms is redefining healthcare, improving the quality of patient personalized care, and delivering value to all stakeholders. This collection of research now stands as a valuable resource, capturing the state-of-the-art in this exciting and emerging field.
- Tài liệuBig Data and Artificial Intelligence: Volume I(MDPI, 2025) Lytras, Miltiadis D.; Serban, Andreea ClaudiaThe Topic “Big Data and Artificial Intelligence” explores the transformative impact of AI and Big Data across diverse domains, highlighting their role as catalysts for innovation, decision-making, and business model evolution. This reprint presents cutting-edge research, covering the full spectrum of AI and Big Data applications, from theoretical foundations to real-world implementations. Key topics include enabling technologies such as machine learning, neural networks, natural language processing, AI agents, analytics, and distributed computing. Methodological advancements, strategic frameworks, and models are examined, addressing areas such as sustainable development, industry innovation, ethical considerations, and social impact. Additionally, the collection showcases best practices, R&D project outcomes, and industry–government collaborations, offering valuable insights into the latest developments in AI-driven decision-making and data ecosystems. Edited by Prof. Miltiadis D. Lytras and Prof. Andreea Claudia Serban, this reprint compiles high-quality contributions from leading researchers and practitioners, providing a comprehensive resource for academics, industry experts, and policymakers interested in the evolving landscape of artificial intelligence and Big Data. The participating journals include Big Data and Cognitive Computing, Future Internet, Information, Remote Sensing, and Sustainability.
- Tài liệuBig Data and Artificial Intelligence: Volume II(MDPI, 2025) Lytras, Miltiadis D.; Serban, Andreea ClaudiaThe Topic “Big Data and Artificial Intelligence” explores the transformative impact of AI and Big Data across diverse domains, highlighting their role as catalysts for innovation, decision-making, and business model evolution. This reprint presents cutting-edge research, covering the full spectrum of AI and Big Data applications, from theoretical foundations to real-world implementations. Key topics include enabling technologies such as machine learning, neural networks, natural language processing, AI agents, analytics, and distributed computing. Methodological advancements, strategic frameworks, and models are examined, addressing areas such as sustainable development, industry innovation, ethical considerations, and social impact. Additionally, the collection showcases best practices, R&D project outcomes, and industry–government collaborations, offering valuable insights into the latest developments in AI-driven decision-making and data ecosystems. Edited by Prof. Miltiadis D. Lytras and Prof. Andreea Claudia Serban, this reprint compiles high-quality contributions from leading researchers and practitioners, providing a comprehensive resource for academics, industry experts, and policymakers interested in the evolving landscape of artificial intelligence and Big Data. The participating journals include Big Data and Cognitive Computing, Future Internet, Information, Remote Sensing, and Sustainability.