Furthermore, the authors delve into the fascinating realm of optimized flexibleantenna arrays for MIMO systems, employing both transparent and non-transparent materials. The development of such arrays entails a meticu...
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Furthermore, the authors delve into the fascinating realm of optimized flexibleantenna arrays for MIMO systems, employing both transparent and non-transparent materials. The development of such arrays entails a meticulous optimization process, where a delicate balance between performance, form factor, and functionality is achieved. By shedding light on this complex process, the book equips readers with the knowledge and tools necessary to engineer high-performing, flexible antenna arrays for advanced wireless communication systems.;The book embraces a broad scope by encompassing various substrate materials and fabrication techniques. This inclusive approach ensures its relevance and applicability to a wide range of readers, including novice researchers, postgraduate students, research scholars, as well as seasoned professionals and experts in the field of antennas hailing from diverse industries and academic institutions.;Moreover, undergraduate students pursuing degrees in Communication engineering, Electronics engineering, and Antennas for Wireless Communication Systems will find this book to be an indispensable resource, offering highly pertinent and enlightening content that bridges the gap between theoretical concepts and real-world antenna design challenges.
Facial expressions convey human emotions and can be categorized into macro-expressions (MaEs) and micro-expressions (MiEs) based on duration and intensity. While MaEs are voluntary and easily recognized, MiEs are invo...
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Facial expressions convey human emotions and can be categorized into macro-expressions (MaEs) and micro-expressions (MiEs) based on duration and intensity. While MaEs are voluntary and easily recognized, MiEs are involuntary, rapid, and can reveal concealed emotions. The integration of facial expression analysis with Internet-of-Thing (IoT) systems has significant potential across diverse scenarios. IoT-enhanced MaE analysis enables real-time monitoring of patient emotions, facilitating improved mental health care in smart healthcare. Similarly, IoT-based MiE detection enhances surveillance accuracy and threat detection in smart security. Our work aims to provide a comprehensive overview of research progress in facial expression analysis and explores its potential integration with IoT systems. We discuss the distinctions between our work and existing surveys, elaborate on advancements in MaE and MiE analysis techniques across various learning paradigms, and examine their potential applications in IoT. We highlight challenges and future directions for the convergence of facial expression-based technologies and IoT systems, aiming to foster innovation in this domain. By presenting recent developments and practical applications, our work offers a systematic understanding of the ways of facial expression analysis to enhance IoT systems in healthcare, security, and beyond.
Recommender systems play a pivotal role in helping users navigate a vast selection of products and services. On online platforms, users have the opportunity to share feedback in various modes, such as numerical rating...
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Recommender systems play a pivotal role in helping users navigate a vast selection of products and services. On online platforms, users have the opportunity to share feedback in various modes, such as numerical ratings, textual reviews, and likes/dislikes. Traditional recommendation systems rely on users’ explicit ratings or implicit interactions (e.g., likes, clicks, shares, and saves) to learn user preferences and item characteristics. Beyond numerical ratings, textual reviews provide insights into users’ fine-grained preferences and item features. Analyzing these reviews is crucial for enhancing the performance and explainability of personalized recommendation results. In this paper, we provide a comprehensive overview of the development in review-based recommender systems over recent years, highlighting the importance of reviews in recommender systems, as well as the challenges associated with extracting features from reviews and integrating them into ratings. Specifically, we introduce a classification scheme in terms of both the integration of reviews into recommendation systems and the technical methodology. Additionally, we summarize the state-of-the-art methods, analyzing their unique features, effectiveness, and limitations. The study also presents the various evaluation metrics, comparative analysis, datasets, and real-world applications of review-based recommendation systems. Finally, we propose potential directions for future research, including multi-modal data integration, multi-criteria rating information, and ethical considerations.
The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November ...
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ISBN:
(数字)9783030638207
ISBN:
(纸本)9783030638191
The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*;* The conference was held virtually due to the COVID-19 pandemic.
The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November ...
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ISBN:
(数字)9783030638238
ISBN:
(纸本)9783030638221
The two-volume set CCIS 1332 and 1333 constitutes thoroughly refereed contributions presented at the 27th International Conference on Neural Information Processing, ICONIP 2020, held in Bangkok, Thailand, in November 2020.*;* The conference was held virtually due to the COVID-19 pandemic.
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