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[null,"1.","Record Nr.",null,"UNISA996465444403316"]
[null,null,"Autore",null,"Wu Zi-Yang"]
[null,null,"Titolo",null,"Efficient Integration of 5G and Beyond Heterogeneous Networks / / by Zi-Yang Wu, Muhammad Ismail, Justin Kong, Erchin Serpedin, Jiao Wang"]
[null,null,"Pubbl/distr/stampa",null,"Springer Singapore, 2020"]
[{"$nulls":4},"Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020"]
[null,null,"ISBN",null,"981-15-6938-X"]
[null,null,"Edizione",null,"[1st ed. 2020.]"]
[null,null,"Descrizione fisica",null,"1 online resource (130 pages) : illustrations"]
[null,null,"Disciplina",null,"004.22"]
[null,null,"Soggetti",null,"Computer organization"]
[{"$nulls":4},"Electrical engineering"]
[{"$nulls":4},"Wireless communication systems"]
[{"$nulls":4},"Mobile communication systems"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Knowledge representation (Information theory) "]
[{"$nulls":4},"Sociophysics"]
[{"$nulls":4},"Econophysics"]
[{"$nulls":4},"Computer Systems Organization and Communication Networks"]
[{"$nulls":4},"Communications Engineering, Networks"]
[{"$nulls":4},"Wireless and Mobile Communication"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Knowledge based Systems"]
[{"$nulls":4},"Data-driven Science, Modeling and Theory Building"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes index."]
[null,null,"Nota di contenuto",null,"Chapter 1. Introduction -- Chapter 2. Efficient Joint Planning of HetNets -- Chapter 3. Realization of Mobile Indoor Channels -- Chapter 4. Data-driven Handover Algorithm in Mobile HetNets -- Chapter 5. Data-driven Multi-homing Resource Allocation in Mobile HetNets -- Chapter 6. Conclusions."]
[null,null,null,"Sommario/riassunto","This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects. The integration of high-frequency air interfaces into 5G+ wireless networks can relieve the congested radio frequency (RF) bands. Visible light communication "]
[{"$nulls":4},"(VLC) is now emerging as a promising candidate for future generations of HetNets. Heterogeneous RF-optical networks combine the high throughput of visible light and the high reliability of RF. However, when implementing these HetNets in mobile scenarios, several challenges arise from both planning and operational perspectives. Since the mmWave, terahertz, and visible light bands share similar wave propagation characteristics, the concepts presented here can be broadly applied in all such bands. To facilitate the planning of RF-optical HetNets, the authors present an algorithm that specifies the joint optimal densities of the base stations by drawing on stochastic geometry in order to satisfy the users’ quality-of-service (QoS) demands with minimum network power consumption. From an operational perspective, the book explores vertical handovers and multi-homing using a cooperative framework. For vertical handovers, it employs a data-driven approach based on deep neural networks to predict abrupt optical outages; and, on the basis of this prediction, proposes a reinforcement learning strategy that ensures minimal network latency during handovers. In terms of multi-homing support, the authors examine the aggregation of the resources from both optical and RF networks, adopting a two-timescale multi-agent reinforcement learning strategy for optimal power allocation. Presenting comprehensive planning and operational strategies, the book allows readers to gain an in-depth grasp of how to integrate future coexisting networks at high-frequency bands in a cooperative manner, yielding reliable and high-speed 5G+ HetNets."]
[null,"2.","Record Nr.",null,"UNINA9910971987803321"]
[null,null,"Titolo",null,"Promoting the emotional well-being in children and adolescents and preventing their mental ill health : a handbook / / edited by Kedar Nath Dwivedi and Peter Brinley Harper ; foreword by Caroline Lindsey"]
[null,null,"Pubbl/distr/stampa",null,"London, : Jessica Kingsley, 2004"]
[null,null,"ISBN",null,"9786610267033"]
[{"$nulls":4},"9781280267031"]
[{"$nulls":4},"1280267038"]
[{"$nulls":4},"9781423709831"]
[{"$nulls":4},"1423709837"]
[{"$nulls":4},"9781846420115"]
[{"$nulls":4},"1846420113"]
[null,null,"Edizione",null,"[1st ed.]"]
[null,null,"Descrizione fisica",null,"1 online resource (290 p.)"]
[null,null,"Disciplina",null,"618.9289"]
[null,null,"Soggetti",null,"Child mental health services"]
[{"$nulls":4},"Mental illness - Prevention"]
[{"$nulls":4},"Teenagers - Mental health services"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"COVER; Promoting the Emotional Well-being of Children and Adolescents and Preventing Their Mental Ill Health: A Handbook; Contents; Foreword; Preface; Acknowledgements; 1. Introduction; 2. Developmental Perspective; 3. Attachment Theory and Mental Health; 4. Emotion Regulation and Mental Health; 5. Attention and Mental Health; 6. Addiction as a Mark of Adulthood: The enduring fascination of drugs and alcohol among adolescents; 7. Parenting; 8. Life Skills Education through Schools; 9. Prevention of Depression and Anxiety in Children and Adolescents; 10. Prevention of Eating Disorders"]
[{"$nulls":4},"11. Promotion of Prosocial Development and Prevention of Conduct Disorders 12. Prevention of Mental Health Problems in Socially Excluded Children and Young People: A model for mental health service pr; 13. Developing Culturally Sensitive Services to meet the Mental Health Needs of Ethnic Minority Children; 14. Ethnic Minority Children and Families and Mental Health: Preventive approaches; 15. The Mental Health Europe Projects and the Greek Perspective; The Contributors; "]
[{"$nulls":4},"Subject Index; Author Index"]
[null,null,null,"Sommario/riassunto","It provides overviews of the key psychological processes affecting mental health, such as development, attachment, emotion regulation, attention and draws out the implications for preventive measures. There is emphasis on the importance of how initiatives in parenting and education can promote children's emotional well-being."]
[null,"3.","Record Nr.",null,"UNINA9911031573803321"]
[null,null,"Autore",null,"Diwakar Manoj"]
[null,null,"Titolo",null,"Machine Learning and Deep Learning Modeling and Algorithms with Applications in Medical and Health Care / / edited by Manoj Diwakar, Vinayakumar Ravi, Prabhishek Singh, Hoang Pham"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025"]
[null,null,"ISBN",null,"3-031-98728-4"]
[null,null,"Edizione",null,"[1st ed. 2025.]"]
[null,null,"Descrizione fisica",null,"1 online resource (521 pages)"]
[null,null,"Collana",null,"Springer Series in Reliability Engineering, , 2196-999X"]
[null,null,"Disciplina",null,"610.153"]
[null,null,"Soggetti",null,"Medical physics"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Algorithms"]
[{"$nulls":4},"Medical care"]
[{"$nulls":4},"Industrial engineering"]
[{"$nulls":4},"Production engineering"]
[{"$nulls":4},"Operations research"]
[{"$nulls":4},"Medical Physics"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Health Care"]
[{"$nulls":4},"Industrial and Production Engineering"]
[{"$nulls":4},"Operations Research and Decision Theory"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"Enhancing dysarthric speech for improved clinical communication: A deep learning approach -- Speech-based real-world scene understanding for assistive care of the visually impaired -- Medical image segmentation with deep learning: An overview -- Lightweight generative model for synthetic biomedical images with enhanced quality -- Pediatric dental disease detection using X-ray image enhancements and deep learning algorithms -- Evaluation of Parkinson disease from MRI images using deep learning techniques -- Analyzing the effect of eyes open and eyes closed states on EEG in Parkinson’s disease with ON and OFF medication -- Automated detection of diabetic retinopathy using ResNet-50 deep learning model -- Deep learning model for decoding subcortical brain activity from simultaneous EEG-FMRI multi-model data -- Secure transmission of "]
[{"$nulls":4},"medical images in IoMT for smart cities using data hiding scheme -- Deep learning approaches to heart stroke prediction: Model evaluation and insights -- Harnessing predictive modeling techniques for early detection and management of diseases: Challenges, innovations, and future directions -- Fundamentals of machine learning and deep learning for healthcare applications -- Automatic detection of Parkinson disease through various machine learning models -- Transforming healthcare: The role of AI and ML in disease prediction, treatment, and patient satisfaction -- Multi-modality medical (CT, MRI, ultrasound etc.) Image fusion using machine learning/deep learning -- Leveraging digital devices for objective behavioral health assessment: Computational machine learning methods for sleep and mental health evaluation -- Optimizing medical image quality through hybrid machine learning techniques and convolutional denoising autoencoders -- Image segmentation in multimodal medical imaging using deep learning models -- Brain MRI analysis for multiple sclerosis detection using deep learning techniques."]
[null,null,null,"Sommario/riassunto","This book explains medical image processing and analysis using deep learning algorithms to analyze medical data. It focuses on the latest achievements and developments in applying this analysis to medical imaging, clinical, and other healthcare applications. The book covers among other areas: Image acquisition and formation. Computer-aided diagnosis. Image classification. Feature extraction. Image enhancement/segmentation. Medical image processing issues such as segmentation, visualization, registration, and navigation may seem to be distinct, yet they are all intertwined in the process of resolving clinical bottlenecks. Using deep learning algorithms, researchers were able to achieve record-breaking performance and set the bar for future research. Due to the extensive quantity of medical imaging data of CT scan, ultrasound, and MRI, there is widespread use of machine learning, specifically deep learning, to discover specific patterns on such data. Such large data is well quantified by deep learning models. Deep learning is now being utilized, customized, and particularly developed for medical image analysis, as opposed to when it was first introduced to the community. Having learned more about the techniques, researchers have come up with innovative ideas for combining artificial intelligence (AI) with neural networks to solve difficult issues like medical image reconstruction. The key features of this book are: Machine learning and deep learning applications. Medical imaging applications. Feature extraction and analysis. Medical image classification, segmentation, recognition, and registration. Medical image analysis and enhancement. <Handling medical image dataset."]