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Advanced prognostic predictive modelling in healthcare data analytics / / Sudipta Roy, Lalit Mohan Goyal, Mamta Mittal, editors
| Advanced prognostic predictive modelling in healthcare data analytics / / Sudipta Roy, Lalit Mohan Goyal, Mamta Mittal, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (317 pages) |
| Disciplina | 610.28563 |
| Collana | Lecture Notes on Data Engineering and Communications Technologies |
| Soggetto topico |
Artificial intelligence - Medical applications
Medical informatics Information visualization Pronòstic mèdic Simulació per ordinador Intel·ligència artificial en medicina Informàtica mèdica Mineria de dades |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 981-16-0538-6 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910483684603321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Advancement of Machine Intelligence in Interactive Medical Image Analysis / / edited by Om Prakash Verma, Sudipta Roy, Subhash Chandra Pandey, Mamta Mittal
| Advancement of Machine Intelligence in Interactive Medical Image Analysis / / edited by Om Prakash Verma, Sudipta Roy, Subhash Chandra Pandey, Mamta Mittal |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (336 pages) |
| Disciplina | 610.28563 |
| Collana | Algorithms for Intelligent Systems |
| Soggetto topico |
Engineering—Data processing
Machine learning Big data Signal processing Image processing Speech processing systems Optical data processing Data Engineering Machine Learning Big Data/Analytics Signal, Image and Speech Processing Image Processing and Computer Vision |
| ISBN | 981-15-1100-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Pragmatic Medical Image Analysis and Deep Learning: An Emerging Trend -- Aspect of Big Data in Medical Imaging to Extract the Hidden Information Using HIPI in HDFS Environment -- Image Segmentation using Deep Learning Techniques -- Application of Machine Intelligence in Digital Pathology: Identification of Falciparum Malaria in Thin Blood Smear Image -- Efficient ANN Algorithms for Sleep Apnea Detection using Transform Methods -- Medical Image Processing in Detection of Abdomen Diseases -- Multi-Reduct Rough Set Classifier for Computer-Aided Diagnosis in Medical Data -- A New Approach of Intuitionistic Fuzzy Membership Matrix in Medical Diagnosis with Application -- Image Analysis and Automation of Data Processing in Assessment of Dental X-ray (OPG) Using MATLAB and Excel VBA -- Detecting Bone Fracture Using Transfer Learning -- GAN based novel approach for data augmentation with improved disease classification -- Automated glaucoma type identification using Machine learning or Deep learning techniques -- Glaucoma Detection from Retinal Fundus Images using RNFL Texture Analysis -- Artificial Intelligence based Glaucoma Detection -- Security Issues of Internet of Things in Health-Care Sector: An Analytical Approach. |
| Record Nr. | UNINA-9910483975203321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Big Data Processing Using Spark in Cloud [[electronic resource] /] / edited by Mamta Mittal, Valentina E. Balas, Lalit Mohan Goyal, Raghvendra Kumar
| Big Data Processing Using Spark in Cloud [[electronic resource] /] / edited by Mamta Mittal, Valentina E. Balas, Lalit Mohan Goyal, Raghvendra Kumar |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIII, 264 p. 89 illus., 62 illus. in color.) |
| Disciplina | 005.7 |
| Collana | Studies in Big Data |
| Soggetto topico |
Big data
Computer security Big Data Systems and Data Security Big Data/Analytics |
| ISBN | 981-13-0550-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Concepts of Big Data and Apache Spark -- Big Data Analysis in Cloud and Machine Learning -- Security Issues and Challenges related to Big Data -- Big Data Security Solutions in Cloud -- Data Science and Analytics -- Big Data Technologies -- Data Analysis with Casandra and Spark -- Spin up the Spark Cluster -- Learn Scala -- IO for Spark -- Processing with Spark -- Spark Data Frames and Spark SQL -- Machine Learning and Advanced Analytics -- Parallel Programming with Spark -- Distributed Graph Processing with Spark -- Real Time Processing with Spark -- Spark in Real World -- Case Studies. . |
| Record Nr. | UNINA-9910739483403321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Computational Methods in Psychiatry
| Computational Methods in Psychiatry |
| Autore | Battineni Gopi |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , 2024 |
| Descrizione fisica | 1 online resource (345 pages) |
| Altri autori (Persone) |
MittalMamta
ChintalapudiNalini |
| Soggetto topico |
Artificial intelligence
Machine learning |
| ISBN |
9789819966370
981996637X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- About the Editors -- Mental Health in Italy During the Pandemic: A Shift from Self-determination to Solidarity? -- 1 Coronavirus and State of Necessity -- 2 The Right to Health as a Fundamental Human Right -- 2.1 Implementation of the Right to Health at International Level -- 3 The Right to Health in the European Context -- 4 Protection of the Right to Health of Persons with Mental Illness in the International Law -- 5 The Right to Health in the Italian Constitution -- 6 From Medical Paternalism to Homo Dignus: The Central Role of the Basaglia Law in the Italian Legal System -- 7 Solidarity as a Principle for Reinterpreting Health and Other Fundamental Rights -- 8 The National Health System to the Test of the Pandemic -- 9 Conclusions -- References -- Analysis of Depression Disorder with Motor Activity Time-Series Data Using Machine Learning and Deep Learning -- 1 Introduction -- 2 Literature Review -- 3 Methods -- 3.1 Dataset -- 3.2 ML Models -- 3.2.1 Logistic Regression -- 3.2.2 Support Vector Machine -- 3.2.3 XGBoost Algorithm -- 3.2.4 Random Forest Method -- 3.2.5 Deep Neural Network -- 3.2.6 Long Short-Term Memory (LSTM) Network -- 3.3 Experimental Setup -- 3.4 ML Model Hyperparameter Tuning -- 3.5 Evaluation Metrics -- 4 Results and Discussion -- 5 Conclusion -- References -- Intelligent Monitoring System Based on ATmega Microcontrollers in Healthcare with Stress Reduce Effect -- 1 Introduction -- 2 Research Background -- 3 Materials and Methods -- 3.1 Project Testing -- 4 Results -- 5 Conclusion -- References -- Predictive Measures to Tackle Mental Disorders During COVID-19 -- 1 Introduction -- 1.1 Why Predictive Measures? -- 1.2 How May Technology Aid? -- 2 Mental Disorders that Can Be Dealt with Computational Technology -- 2.1 Anxiety Disorder -- 2.1.1 Phobia and Panic Disorder Triggered during the Pandemic.
2.1.2 Generalized Anxiety Disorder (GAD) -- 2.1.3 Post-Traumatic Stress Disorder (PTSD) -- 2.1.4 Obsessive-Compulsive Disorder (OCD) -- 2.2 Mood Disorder -- 2.2.1 Depression -- 2.2.2 Bipolar Disorder -- Bipolar I Disorder -- Bipolar II Disorder -- Cyclothymic Disorder (Cyclothymia) -- 2.3 Sexual Disorder -- 2.3.1 Paraphilia Disorder -- 2.4 Traditional Predictive Measures in Psychology to Assess Mental Disorders -- 2.4.1 Life History of Patients -- 2.4.2 Assessment Interviews and Behavioral Observations -- 2.4.3 Psychological Tests -- 2.4.4 Biological Predictive Measures for Mood, Anxiety, and Sexual Disorders -- 2.5 Use of Computational Technology as a Predictive Measure for Anxiety, Mood, and Sexual Disorders -- 3 Major Computing Technologies for Tackling Mental Disorders -- 3.1 Internet of Things (IoT) -- 3.2 Emerging Mobile Applications -- 3.3 Machine Learning/Deep Learning -- 3.4 Big Data Analytics -- 3.5 Assistive Technologies -- 3.6 Federated Learning -- 4 Challenges Associated with Use of Computing for Mental Health Management -- 4.1 Data Acquisition -- 4.2 Consent -- 4.3 Confidentiality -- 4.4 Lack of Legislation -- 4.5 Reliability Issues -- 5 Summary -- References -- Intelligent Digital Monitoring of the Levels of Stress -- 1 Introduction -- 2 Measurement of Stress Levels -- 2.1 Wearable Devices -- 2.2 Behavioural Coding -- 2.2.1 Self-Reporting -- 2.2.2 Physiological Measuring Tools -- 2.2.3 Heart Rate Variability Analysis -- 2.2.4 Psychosocial Approach -- 2.2.5 Perceived Stress Scale -- 2.2.6 Measuring Salivary and Hair Cortisol -- 2.2.7 Pupil Dilation Measurement -- 2.2.8 Electroencephalography -- 2.2.9 Speech Analysis -- 2.2.10 Computer Mouse Usage -- 3 Digital Monitoring of Stress Levels -- 3.1 Intelligent Wireless Sensor Systems -- 3.2 Personal Digital Assistance -- 3.3 Mobile Applications. 3.4 Bioelectronics and Digital Signal Processing -- 3.5 Cognitive Behavioural Therapy and Conversational Chatbots -- 4 Role of Recent Technological Trends in Real-Time Stress Detection -- 4.1 Machine Learning -- 4.2 Deep Learning -- 4.3 Internet of Things -- 4.4 Brain-Inspired Computing -- 4.5 Natural Language Processing -- 5 Conclusions and Future Research Directions -- References -- Consequences of Brain Health in the Digital Era -- 1 Introduction -- 1.1 Attention Deficit Disorders -- 1.2 Impairments in Emotional and Social Intelligence -- 1.3 Physical Effects -- 1.3.1 Mental Health -- 1.3.2 Social Health -- 1.3.3 Impact on Cognitive and Brain Development -- 1.3.4 Sleeping Patterns -- 1.3.5 Effects on Brain Functions -- 2 Technological Interventions to Monitor and Protect from the Harmful Effects on Brain Health in a Digital Era -- 2.1 Method of Cognitive Training to Improve Brain Health -- 2.2 Cognitive Behavioral Therapy -- 2.3 Meditation Apps -- 2.4 Wearable Technology -- 2.5 Virtual Reality Technology -- 2.6 Brain Stimulation Devices -- 2.7 Online Therapy Platforms -- 3 Benefits of the Digital Era on Brain Health -- 3.1 Neural Exercises -- 3.2 Access to Information -- 3.3 Improved Multitasking Skills -- 3.4 Working Memory and Fluid Intelligence -- 3.5 Visual Attention Reaction Time -- 3.6 Telemedicine -- 4 Discussions -- 5 Conclusions -- References -- Brain Health in the Digital Era -- 1 Introduction -- 2 Digital Era and Mental Health of Children -- 2.1 Digital Era and Issues Related to Security, Privacy, and Mental Health of Teenagers -- 2.2 Cyberstalking and Female Mental Health -- 2.3 Revenge Porn and Brain Health -- 3 Impact of Videogames on Brain Health -- 3.1 Virtual Reality and Brain Health -- 3.2 Use of Digital Technologies for Augmenting and Supporting Mental Health -- 3.3 Telemedicine Based Technologies to Improve Mental Health. 4 Screen Time and Mental Health -- 4.1 Suicide and Digital Technologies -- 4.2 Radicalization in the Digital Era -- 4.3 Family Functioning and Digital Era -- 5 Impact of Remote Working During COVID-19 on Mental Health -- 6 Conclusion -- References -- Work from Home and its Impact on Lifestyle of Humanoid in the Context of COVID-19 -- 1 Introduction -- 2 Literature Survey -- 2.1 Work from Home -- 2.2 Level of Living -- 2.2.1 Job Satisfaction of Staff in Home Offices -- 3 Methods -- 3.1 Techniques: Sample -- 3.1.1 Data Gathering -- 3.1.2 Questionnaire -- 3.1.3 Demographic Data -- 4 Discussion -- 4.1 Did the Concept of Work from Home Affect the Efficiency of Work? -- 4.2 Did the Concept of Work from Home Affect Timings of Work? -- 4.3 Did the Concept of Work from Home Affect Family Space? -- 4.4 Did the Concept of Work from Home Affect Work Satisfaction? -- 4.5 Did the Concept of Work from Home Affect Time Management? -- 4.5.1 Improved Timeliness -- 4.5.2 Improved Job Standards -- 4.5.3 Greater Output -- 4.5.4 Decreased Stress and Anxiety -- 5 Conclusion -- References -- Deep Feedforward Neural Networks for Prediction of Mental Health -- 1 Introduction -- 2 Psychiatry Tools -- 2.1 Electroencephalogram (EEG) -- 2.2 QEEG -- 3 Feedforward Neural Networks -- 4 Discussion -- 5 Conclusions -- References -- The Challenge of Self-diagnosis on Mental Health Through Social Media: A Qualitative Study -- 1 Introduction -- 2 Self-diagnosis, Mental Health, and Social Media -- 3 Descriptive Study -- 3.1 Descriptive Evidence -- 3.2 A Model: The Link Between Social Media Usage, Self-diagnosis, and Mental Health -- 4 Conclusion and Discussion -- References -- Relationship Between Mortality and Mental Health Disorders -- 1 Introduction -- 2 Material and Method -- 2.1 Thirthahalli Is a Taluk of Shimoga District of Karnataka. 2.1.1 Indicators of the Mortality Rate in Karnataka for Schizophrenia Include -- 2.1.2 Participants -- 2.1.3 Mortality Data -- 3 Results -- 4 Discussion -- References -- Recent Developments in the Application of Computer-Aided Drug Design in Neurodegenerative Disorders -- 1 Introduction -- 2 Neurodegenerative Diseases -- 2.1 Parkinson's Diseases -- 2.2 Alzheimer's Disease -- 2.3 Huntington's Disease -- 2.4 Amyotrophic Lateral Sclerosis (ALS) -- 2.5 Motor Neuron Disease -- 3 New Trends in Drug Discovery -- 4 Computer-Aided Drug Design Methods -- 4.1 Drug Targets -- 4.2 Statistical Methods -- 4.3 Pharmacophore Modeling -- 4.4 Virtual Screening -- 4.5 Docking and Molecular Dynamics -- 5 Stages of Drug Design -- 5.1 Target Identification and Validation -- 5.2 Hit Identification -- 5.3 Lead Discovery -- 5.4 Structure of Target Protein -- 5.5 Structure-Based De Novo Design -- 5.6 Database Searching -- 5.7 Lead Optimization -- 5.8 Binding Affinity Prediction -- 5.9 Efficient Approaches -- 5.10 Preclinical and Clinical Studies -- 6 Current Scenario and Future Scope of Computer-Aided Drug Designing in the Management of Neurodegenerative Disorders -- References -- Student Stress Detection in Online Learning During Outbreak -- 1 Introduction -- 2 Degree of Stress -- 2.1 Stress Classification -- 2.2 The Impact of Stress on Human Body -- 2.2.1 Respiratory Systems -- 2.2.2 Cardiovascular System -- 2.2.3 Endocrine System -- The HPA Axis -- 2.2.4 Gastrointestinal System -- Exophages -- Stomach -- Bowel -- 2.2.5 Nervous System -- 2.2.6 Male Reproductive System -- Sexual Desire -- Reproduction -- Diseases of the Reproductive System -- 2.2.7 Female Reproductive System -- Menstruation -- Sexual Desire -- Pregnancy -- Premenstrual Syndrome -- Menopause -- Diseases of the Reproductive System -- 3 Stress Characteristics and Impact of Technology Rise. 3.1 Distinct Challenging Stressor Among Students During COVID-19. |
| Record Nr. | UNINA-9910768194003321 |
Battineni Gopi
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| Singapore : , : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data intensive computing applications for big data / / edited by Mamta Mittal [and three others]
| Data intensive computing applications for big data / / edited by Mamta Mittal [and three others] |
| Pubbl/distr/stampa | Amsterdam ; ; Berlin ; ; Washington, DC : , : IOS Press, , [2018] |
| Descrizione fisica | 1 online resource (618 pages) |
| Disciplina | 005.7 |
| Collana | Advances in parallel computing |
| Soggetto topico | Big data |
| ISBN | 1-61499-814-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910795039503321 |
| Amsterdam ; ; Berlin ; ; Washington, DC : , : IOS Press, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Data intensive computing applications for big data / / edited by Mamta Mittal [and three others]
| Data intensive computing applications for big data / / edited by Mamta Mittal [and three others] |
| Pubbl/distr/stampa | Amsterdam ; ; Berlin ; ; Washington, DC : , : IOS Press, , [2018] |
| Descrizione fisica | 1 online resource (618 pages) |
| Disciplina | 005.7 |
| Collana | Advances in parallel computing |
| Soggetto topico | Big data |
| ISBN | 1-61499-814-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910827929603321 |
| Amsterdam ; ; Berlin ; ; Washington, DC : , : IOS Press, , [2018] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Deep Learning Techniques for Biomedical and Health Informatics / / edited by Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen
| Deep Learning Techniques for Biomedical and Health Informatics / / edited by Sujata Dash, Biswa Ranjan Acharya, Mamta Mittal, Ajith Abraham, Arpad Kelemen |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (395 pages) |
| Disciplina | 006.31 |
| Collana | Studies in Big Data |
| Soggetto topico |
Computational intelligence
Engineering—Data processing Biomedical engineering Big data Artificial intelligence Computational Intelligence Data Engineering Biomedical Engineering and Bioengineering Big Data Artificial Intelligence |
| ISBN | 3-030-33966-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | MedNLU: Natural Language Understander for Medical Texts -- Deep Learning Based Biomedical Named Entity Recognition Systems -- Disambiguation Model for Bio-Medical Named Entity Recognition -- Applications of Deep Learning in Healthcare and Biomedicine -- Deep Learning for Clinical Decision Support Systems: A Review from the Panorama of Smart Healthcare -- Review of Machine Learning and Deep Learning based Recommender Systems for Health Informatics -- Deep Learning and Explainable AI in Healthcare using EHR -- Deep Learning for Analysis of Electronic Heath Records -- Bioinformatics Using Deep Architecture -- Intelligent, Secure Big Health Data Management using Deep Learning and Blockchain Technology: An Overview -- Malaria Disease Detection using CNN Technique with SGD, RMSprop and ADAM Optimizers -- Deep Reinforcement Learning based Personalized Health Recommendations. |
| Record Nr. | UNINA-9910483376403321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Energy Conservation for IoT Devices : Concepts, Paradigms and Solutions / / edited by Mamta Mittal, Sudeep Tanwar, Basant Agarwal, Lalit Mohan Goyal
| Energy Conservation for IoT Devices : Concepts, Paradigms and Solutions / / edited by Mamta Mittal, Sudeep Tanwar, Basant Agarwal, Lalit Mohan Goyal |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XII, 356 p. 138 illus., 109 illus. in color.) |
| Disciplina | 006.3 |
| Collana | Studies in Systems, Decision and Control |
| Soggetto topico |
Computational intelligence
Control engineering Robotics Mechatronics Application software Big data Computational Intelligence Control, Robotics, Mechatronics Information Systems Applications (incl. Internet) Big Data |
| ISBN | 981-13-7399-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | IoT Architecture for Preventive Energy Conservation of Smart Buildings -- Designing Energy Efficient IoT based Intelligent Transport System: Need, Architecture, Characteristics, Challenges and Applications -- Energy-Efficient System Design for Internet of Things (IoT) Devices -- Need and Design of Smart and Secure Energy Efficient IoT Based Healthcare Framework -- The Rudiments of Energy Conservation and IoT -- Capacity Estimation of Electric Vehicle Aggregator for Ancillary Services to the Grid -- Existing Enabling Technologies and Solutions for Energy Management in IoT -- Medical Information Processing Using Smartphone Under IoT Framework. |
| Record Nr. | UNINA-9910484111203321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Energy Conservation Solutions for Fog-Edge Computing Paradigms
| Energy Conservation Solutions for Fog-Edge Computing Paradigms |
| Autore | Tiwari Rajeev |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (314 pages) |
| Altri autori (Persone) |
MittalMamta
GoyalLalit Mohan |
| Collana | Lecture Notes on Data Engineering and Communications Technologies Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-16-3448-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- Energy-Aware Resource Scheduling in FoG Environment for IoT-Based Applications -- 1 Introduction -- 1.1 Why FoG Computing? -- 1.2 FoG Application Areas in Smart City -- 1.3 Motivation -- 1.4 Contributions -- 1.5 Organization of Work -- 2 Need of FoG Computing -- 2.1 QoS Parameters -- 3 Energy-Aware Survey in Green-IoT -- 4 Related Work -- 4.1 Resource Allocation and Provisioning in Cloud Computing -- 4.2 Resource Allocation and Provisioning in Fog Computing -- 5 Energy Resource Scheduling Algorithms and Intersection of Parameters in Smart City (Smart Homes) -- 6 Future Scope -- References -- DoSP: A Deadline-Aware Dynamic Service Placement Algorithm for Workflow-Oriented IoT Applications in Fog-Cloud Computing Environments -- 1 Introduction -- 2 Motivation Scenario -- 2.1 Sensing Module -- 2.2 Data Aggregation Module -- 2.3 Data Analysis Module -- 2.4 Decision Making -- 2.5 Actuation Module -- 3 Related Work -- 3.1 Building and Deployed Fog-Based IoT Applications -- 3.2 Resource Allocation for IoT Applications in Fog Environment -- 3.3 Service Placement in Fog Environment -- 3.4 A Qualitative Comparison -- 4 System Model -- 4.1 Application Prioritizing Phase -- 4.2 Node Selection Phase -- 4.3 IoT Application Placement Flow in Fog Environment -- 5 Proposed Methodology -- 5.1 Overview of the Proposed Work -- 5.2 Functional Details of the Proposed Work -- 5.3 Deadline-oriented Service Placement Algorithm (DoSP) -- 6 Performance Evaluation -- 6.1 System Setup and Parameters -- 6.2 Experimental Results -- 7 Conclusion and Future Work -- References -- Improvement of Task Offloading for Latency Sensitive Tasks in Fog Environment -- 1 Introduction -- 2 Cloud, Edge and Fog Computing -- 3 Literature Review -- 4 Smart Flower Optimization Algorithm -- 5 Application of SFOA to Task Offloading Problem.
6 Simulations and Results -- 7 Conclusion -- References -- A Sustainable Energy Efficient IoT-Based Solution for Real-Time Traffic Assistance Using Fog Computing -- 1 Introduction -- 1.1 Vehicle Tracking System -- 1.2 Need of Vehicle Tracking -- 1.3 Problem Statement -- 2 Related Work -- 3 Background -- 3.1 IoT -- 3.2 Cloud Computing -- 3.3 Fog Computing -- 3.4 Cloud, Fog, and IoT -- 4 Proposed Architecture -- 4.1 Problem Formulation and Solution -- 5 Simulation and Results -- 6 Conclusion -- References -- Analysis on Application of Fog Computing in Industry 4.0 and Smart Cities -- 1 Introduction -- 2 Overview of Fog Computing -- 3 Overview of Industry 4.0 and Smart Cities -- 4 Related Studies -- 5 A Fog Computing Enabled Smart City -- 6 Facilitating Industry 4.0 Using Fog Computing Architecture -- 7 Three-Layered Fog-Based IoT Architecture for Industry 4.0 -- 8 Advantages of Using Fog Computing for Industry 4.0 and Smart Cities -- 9 Conclusion -- References -- Fog-Computing: A Novel Approach for Cloud-Based Devices Using Perceptual Cloning Manifestation-PerColNif Taxonomy by Energy Optimization -- 1 Introduction -- 1.1 Fog as Eminent Computing Paradigm -- 2 Related Works -- 2.1 Cloud Computing Era in Health Care Services -- 2.2 Cloud Computing for Vehicle Tracking-Accident Detection Systems -- 2.3 Fog Computing Versus Cloud Computing for Time-Sensitive Applications -- 2.4 Virtual Clusters-Fog Bridging Cloud with Edge Devices -- 3 Tri-Layered Proposed Architecture -- 4 Proposed Taxonomy-Fog-Computing-PerColNif-Taxonomy -- 4.1 Perceptual Cloudlet Cloning Manifestation Process [PerColNif] -- 4.2 PerColNif-Algorithm Implementation -- 4.3 Replacement Services-Node-Node Communication -- 5 Fog-Computing Implementation -- 5.1 Algorithm: ADT-Relax Mode-Quick Mode Sensor Node-Accident Detection Unit -- 5.2 Algorithm-Fog Node Execution. 6 Advantages of PerColNif Using Fog-Computation -- 7 Energy Efficiency Performance Analysis -- 8 Open Challenges on Future Fog-Era -- 9 Conclusion -- References -- Performance Evaluation and Energy Efficient VM Placement for Fog-Assisted IoT Environment -- 1 Introduction -- 1.1 Motivation -- 2 Related Work -- 3 System Model -- 4 Performance Measures -- 5 Profit and Revenue Analysis of the System -- 6 The Energy Model of the Fog System -- 6.1 VM Placement Problem Formulation -- 6.2 Greedy Heuristic Algorithm for Energy Saving -- 6.3 An Illustration -- 6.4 Simulation Results -- 7 Conclusion -- References -- Load Balancing in Fog Computing Using QoS -- 1 Introduction -- 1.1 Fog Computing Architecture Layers -- 1.2 Fog Computing Elementary Layers -- 1.3 Communication Workflow in Fog Environment -- 2 Related Work -- 2.1 Cyber Foraging -- 2.2 Cloudlet -- 3 Proposed Framework -- 3.1 Optimized Load Balancing Algorithm (OLBA) -- 3.2 Environmental Setup -- 4 Results and Discussions -- 4.1 Turn Around Time Performance Test -- 4.2 Fog Resources Resource Utilization -- 4.3 Average Response Time -- 4.4 Processing Delay -- 5 Conclusion and Future Scope -- References -- Fog Computing in Industry 4.0: Applications and Challenges-A Research Roadmap -- 1 Introduction -- 1.1 Fog Computing -- 1.2 Industry 4.0 -- 2 Fog Architecture for Industrial Processes -- 3 Fog Equipped Industrial IoT -- 3.1 Transportation -- 3.2 Smart Grids -- 3.3 Mining -- 3.4 Agriculture -- 3.5 Food Industry -- 3.6 Waste Management -- 3.7 Parking -- 4 Fog Computing in Industry 4.0 -- 4.1 Industrial Internet of Things -- 4.2 Big Data -- 4.3 Cloud Computing -- 4.4 Advancement in Robotics -- 4.5 Smart Manufacturing -- 4.6 Flexibility in Machines -- 4.7 Smart City Applications -- 4.8 Smart Factory Applications -- 4.9 Predictable Maintenance -- 4.10 Augmentative Reality -- 5 Research Challenges. 5.1 Heterogeneity -- 5.2 Security -- 5.3 Programmability -- 5.4 Interoperability -- 5.5 Energy Consumption -- 5.6 Quality of Service (QoS) -- 5.7 Cost -- 6 Conclusions -- References -- Fog Computing Based Architecture for Smart City Projects and Applications -- 1 Introduction -- 1.1 Fog Computing and IoT -- 1.2 Fog Computing Versus Cloud Computing -- 1.3 Contribution -- 2 Related Work -- 3 Smart City Projects in India -- 3.1 Industry 4.0 and Smart City Projects -- 4 Role of Fog Computing in Industry 4.0 for Smart City Projects -- 5 Fog Computing Use Cases for Smart City Projects -- 5.1 Smart Waste Management -- 5.2 IoT-Based Smart Waste Management Systems -- 5.3 Proposed Fog Computing Based Smart Waste Management Architecture -- 5.4 Execution Flow of Proposed Smart Waste Management Architecture -- 5.5 Smart Parking -- 5.6 IoT Based Smart Parking Architectures -- 5.7 Proposed Fog Computing Based Smart Parking Architecture -- 5.8 Execution Flow of Proposed Architecture -- 6 Conclusion -- 7 Future Work -- References -- Integration of Fog Computing and IoT-Based Energy Harvesting (EHIoT) Model for Wireless Sensor Network -- 1 Introduction -- 2 Background -- 2.1 Medical Sensors -- 2.2 IoT and Fog Computing in Smart Healthcare -- 2.3 Energy Consumption Models -- 3 Related Works -- 4 Proposed Design -- 4.1 Design of an IoT/Fog-Based WSN Model for Hospital Environment -- 4.2 Design of the Energy Consumption Model -- 4.3 Design of IoT-Based Energy Harvesting Model (EHIoT) -- 5 Conclusion -- References -- Design and Development of Efficient Secure Routing Mechanism for Wireless Sensor Network -- 1 Background -- 2 High-Level Techniques (HIT) -- 3 Problem Description -- 4 Study Objectives -- 5 Literature Review -- 5.1 Literature Survey Based on Hierarchical Routing Protocols -- 5.2 Existing Research Work on Delay Concept in Routing for WSN. 6 Energy-Efficient and Security-Aware Routing Protocols -- 6.1 FEESR Design Methodology -- 6.2 FEESR Algorithm Design and Implementation -- 6.3 Feesr Numerical Analysis and Outcome Comparison -- 6.4 Result Analysis -- 7 Conclusion -- 7.1 Scope and Limitations of the Study -- 7.2 Future Scope of Applicability -- References -- Futuristic Communication Systems Using Mobile Edge Computing -- 1 Introduction -- 2 Outline of MEC and 5G -- 2.1 Fundamentals of MEC -- 2.2 Integration of MEC with 5G Systems -- 3 Overview of MEC/5G Researches -- 3.1 Internet of Things (IoT) Leveraging MEC -- 3.2 MEC with NOMA -- 3.3 MEC with Heterogeneous CRAN -- 3.4 MEC with UAV Communications -- 3.5 MEC with WPT and EH -- 4 Conclusions -- References -- Methodology to Ensure the Continuity of the Information Systems Service, Based on the Monitoring of Electrical Energy, Using IoT Technology -- 1 Introduction -- 2 Materials and Methods -- 2.1 Literature Review -- 2.2 Analysis of IoT Devices -- 2.3 Choice of Devices to Implement the Methodology -- 2.4 Device Configuration -- 2.5 Performance Analysis -- 2.6 Interpretation of Results -- 3 Results -- 3.1 Server Unit -- 3.2 Power and Control Units -- 3.3 Monitoring Units -- 3.4 Communication Units -- 3.5 Cooling Unit -- 3.6 Acquisition Units -- 3.7 IoT Units -- 3.8 Display Unit -- 4 Conclusions -- References. |
| Record Nr. | UNINA-9910502640203321 |
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Tiwari Rajeev
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| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Information and communication technology (ICT) frameworks in telehealth / / Mamta Mittal and Gopi Battineni, editors
| Information and communication technology (ICT) frameworks in telehealth / / Mamta Mittal and Gopi Battineni, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] |
| Descrizione fisica | 1 online resource (272 pages) |
| Disciplina | 610.285 |
| Collana | TELe-Health |
| Soggetto topico | Medical telematics |
| ISBN | 3-031-05049-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910588595003321 |
| Cham, Switzerland : , : Springer Nature Switzerland AG, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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