Excavations at Kalopsidha and Ayios Iakovos in Cyprus / by Paul Astrom ; with contributions by several scholars

• Record Nr.: UNISALENTO991000044309707536
• Autore: Astrom, Paul
• Pubbl/distr/stampa: Lund : Boktryckeri, 1966
• Descrizione fisica: 234 p., [51] p. di tav.
• Collana: Studies in Mediterranean archaeology ; 2
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia

Managing Pain in Children : A Clinical Guide for Nurses and Healthcare Professionals

• Record Nr.: UNINA9910795808503321
• Autore: Twycross Alison
• Pubbl/distr/stampa: Hoboken : , : John Wiley & Sons, Incorporated, , 2013; ©2014
• ISBN: 9781118514634; 9780470670545
• Edizione: [2nd ed.]
• Descrizione fisica: 1 online resource (314 pages)
• Altri autori (Persone): DowdenStephanie; StinsonJennifer
• Disciplina: 618.920472
• Soggetti: Pain Management - nursing; Electronic books.
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Cover -- Title page -- Copyright page -- Contents -- List of Contributors -- Foreword -- CHAPTER 1: Why Managing Pain in Children Matters -- Introduction -- What is Pain? -- Consequences of ; Unrelieved Pain -- Children's Views about the Effectiveness of Pain Management -- Misconceptions about Pain -- Factors Affecting Healthcare Professionals' Perceptions of Pain -- Pain Management Standards -- How Effective are Current Pain Management Practices? -- Professional Accountability and Evidence-Based Practice -- Managing Pain in Children is an Ethical Imperative -- Summary -- References -- CHAPTER 2: Anatomy and Physiology of Pain -- Introduction -- The Nervous System -- Misconceptions about the Physiology of Pain in Children -- Pain Mechanisms -- Transduction: The conversion of stimuli to electrical impulses -- Transmission: Conveying impulses to the central nervous system -- Perception -- Modulation -- Visceral Pain -- Physiology of Chronic and Neuropathic Pain -- Central sensitisation in chronic pain -- Nervous System Development and Pain Sensation in Early Life -- Summary -- References -- CHAPTER 3: Pain: A Biopsychosocial Phenomenon -- Introduction -- Biological Factors -- Age -- Cognitive development -- Genetics -- Temperament -- Psychological Factors -- Fear -- Previous experiences of pain -- Social Factors -- Culture -- Family learning -- Gender -- Summary -- References -- CHAPTER 4: Pharmacology of Analgesic Drugs -- Introduction -- Misconceptions -- Addiction, Tolerance and Dependence -- Addiction risk -- Opioid weaning protocols -- How Drugs Work -- Pharmacodynamics -- Pharmacokinetics -- Routes of Drug Administration -- Selection of Analgesic Drugs -- WHO analgesic ladder -- Non-Opioid Analgesic Drugs -- Paracetamol (acetaminophen) -- Nonsteroidal anti-inflammatory drugs -- Opioid Analgesic Drugs -- Tramadol -- Opioid antagonists.; Adjuvant Analgesic Drugs -- Local anaesthetics -- Ketamine -- Other adjuvant analgesic drugs -- Managing and Minimising the Non-Medical Use of Opioids -- Summary -- References -- CHAPTER 5: Physical and Psychological Methods of Pain Relief in Children -- Introduction -- Physical Pain-Relieving Methods -- Acupuncture -- Heat and cold -- Massage -- Psychological Pain-Relieving Methods -- Biofeedback -- Cognitive behavioural therapy -- Distraction -- Hypnosis -- Music therapy -- Relaxation -- Physical Methods of Pain Relief for Neonates -- Breastfeeding -- Facilitated tucking (or containment) -- Kangaroo care (skin-to-skin contact) -- Non-nutritive sucking -- Sucrose -- Swaddling -- Summary -- References -- CHAPTER 6: Pain Assessment -- Introduction -- Healthcare Professionals' Role in Pain Assessment -- Pain Measurement and Pain Assessment -- Assessing Pain in Children -- Step 1: Taking a pain history -- Step 2: Assessing the child's pain using an developmentally appropriate pain assessment tool -- Self-report tools -- Behavioural tools -- Physiological indicators -- Pain Assessment Tools for Neonates -- Pain Assessment in Ventilated Children -- Pain Assessment in Cognitively Delayed Children -- Choosing the Right Pain Assessment Tool -- How Often Should Pain be Assessed? -- Documentation -- Summary -- Key to Case Studies -- References -- CHAPTER 7: Managing Acute Pain in Children -- Introduction -- What is Acute Pain? -- Causes of Acute Pain in Childhood -- Injury -- Childhood illnesses -- Surgery/medical investigations -- Medical conditions -- Developmental disabilities -- Pain Assessment -- Physical and Psychological Interventions -- Pharmacological Interventions -- Non-opioids -- Opioids -- Local anaesthetics -- Regional anaesthesia -- Pain Management Guidelines -- Aims of Pain Management -- World Health Organization (WHO) analgesic ladder.; Pain management in the community setting -- Pain management in the hospital setting -- Suggested Pain Management Regimes for Acute Pain -- Non-opioid analgesia -- Opioid analgesia -- Patient-controlled ; analgesia -- Other analgesic infusions -- Optimising the Safety of Analgesic Drugs -- Managing Adverse Effects of Opioids -- Sedation/respiratory depression -- Nausea and vomiting -- Urinary retention -- Pruritus (itch) -- Constipation -- Regional Anaesthesia -- Central blocks -- Peripheral blocks -- Optimising the Safety of Regional Anaesthesia -- Best practice management for regional analgesia -- Problem solving -- Complications of Regional Anaesthesia -- Pain Problem-Solving -- Transition to Oral Analgesics -- Weaning PCA -- Weaning regional anaesthesia infusions -- Pain medications at home -- Summary -- Key to Case Studies -- References -- CHAPTER 8: Chronic Pain in Children -- Introduction -- What is Chronic Pain? -- How Common is Chronic Pain in Children? -- Aetiology or Causes of Chronic Pain -- Common Chronic Pain Conditions in Children and Adolescents -- Headache -- Chronic abdominal pain -- Musculoskeletal pain -- Neuropathic pain -- Common Types of Neuropathic Pain Conditions -- Complex regional pain syndrome -- Phantom limb pain -- Pain Associated with Sickle Cell Disease -- Factors Triggering and Maintaining Chronic Pain -- Pain-Related Disability -- The Impact of Chronic Pain on the Child and Family -- The Cost of Chronic Pain -- Management of Chronic Pain -- Physical and psychological methods of pain relief -- Physical pain-relieving interventions -- Psychological therapies -- Sleep hygiene -- Complementary and alternative medicine -- Pharmacological interventions -- Invasive therapies -- Multidisciplinary approach -- Chronic pain clinics -- Long-term outcomes -- Summary -- Key to Case Studies -- References.; CHAPTER 9: Palliative Care in Children -- Introduction -- What is Palliative Care? -- What is Paediatric Palliative Care? -- Death in Childhood -- Causes of death in childhood -- Where do children die? -- How Many Children Need Palliative Care? -- Conditions Requiring Paediatric Palliative Care -- Where is Palliative Care for Children Delivered? -- Challenges of home-based palliative care -- When Should Palliative Care be Implemented? -- Evidence Base for Palliative Care -- Research priorities in paediatric palliative care -- Quality in Palliative Care -- Symptoms in Children Receiving Palliative Care -- Pain and Symptom Management -- Types of pain seen in PPC -- Pain Assessment -- Frequency of pain assessment -- Choosing pain-relieving interventions -- Managing Pain in Palliative Care -- Management of intermittent/episodic pain -- Management of persistent pain -- Managing common opioid adverse drug effects -- Managing breakthrough pain -- Adjusting analgesia regimes -- Pain crisis -- Opioid rotation or switching -- Intractable pain and palliative sedation -- Other Pain-Relieving Interventions -- Management of Non-Pain Symptoms -- Assessing non-pain symptoms -- When to treat non-pain symptoms -- Physical and Psychological Methods to Relieve Pain and Other Distressing Symptoms -- Misconceptions Relating to Paediatric Palliative Care -- Ethical and Legal Issues in Paediatric Palliative Care -- Futility in medical management -- Euthanasia versus double effect -- End-of-Life Care -- Causes of pain and distressing symptoms at EOL -- Diagnosing dying -- Management of dying -- After Death -- Family bereavement care -- Staff support -- Summary -- Key to Case Studies -- References -- CHAPTER 10: Management of Painful Procedures -- Introduction -- Procedure-Related Pain: Definition and Prevalence -- Why is it Important to Manage Procedural Pain Effectively?.; Factors that Influence a Child's Response to Painful Procedures -- Managing Procedural Pain: General Principles -- Before the procedure -- During the procedure -- After the procedure -- Using Nitrous Oxide ; to Manage Procedural Pain -- Using Sedation to Manage Procedural Pain -- Issues Relating to the Management of Specific Types of Procedural Pain -- Needle-related pain -- Topical local anaesthetics -- Cryotherapy -- Pain related to burn wound care -- Pain related to cancer investigations -- Pain related to immunisations -- Procedural pain management in neonates -- Summary -- Key to Case Studies -- References -- CHAPTER 11: Where To From Here? -- Introduction -- Reasons for Suboptimal Practices -- Knowledge deficits -- Beliefs about pain in children -- Decision-making strategies -- Organisational culture -- The Way Forward: Using a Knowledge Translation Model as a Framework for Improving Practice -- Evidence -- Context -- Facilitating change -- Researching Children's Pain -- Areas for Future Research -- Summary -- References -- Index.
• Sommario/riassunto: Providing an evidence-based, practical guide to care in all areas of children's pain management, Managing Pain in Children offers nurses and other healthcare professionals an introduction to the skills and expertise to manage children's pain effectively. This fully-updated second edition first explores the relevant anatomy and physiology of children, the latest policy guidelines surrounding pain management and ethical issues involved in managing children's pain. Various pain assessment tools available for children and non-drug methods of pain relief are then explored and applied to practice in relation to acute pain, chronic pain, palliative care and the management of procedural pain. The evidence base, assessment techniques, pain-relieving interventions, and guidance for best practice in both hospital and community settings are covered throughout, making this title an ideal resource for all nurses and healthcare professionals working with children.

Real-Time Cloud Computing and Machine Learning Applications

• Record Nr.: UNINA9911009290703321
• Autore: Fowdur Tulsi Pawan
• Pubbl/distr/stampa: New York : , : Nova Science Publishers, Incorporated, , 2021; ©2021
• ISBN: 1-5361-9813-7
• Descrizione fisica: 1 online resource (810 pages)
• Collana: Computer Science, Technology and Applications
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Intro -- Contents -- Preface -- Chapter 1 -- Introduction -- 1.1. Overview of Cloud Computing, Its Benefits and Applications -- 1.1.1. Benefits of Cloud Computing -- 1.1.2. Applications of Cloud Computing -- 1.1.2.1. Cloud Application Development -- 1.1.2.2. Cloud as an Enabler for Industry 4.0 -- 1.1.2.3. Cloud Radio Access Networks (C-RAN) -- 1.1.2.4. Big Data Analytics -- Cloud Private Branch Exchange (PBX) -- 1.2. Overview of Machine Learning and AI -- 1.2.1. Benefits of Machine Learning and AI -- 1.2.2. Applications of Machine Learning and AI -- 1.3. Combining AI with Cloud Computing for Real-Time Applications -- 1.4. Book Overview -- References -- Chapter 2 -- Cloud Computing Fundamentals -- 2.1. Definitions of Cloud Computing -- 2.2. Computing Paradigms -- 2.3. Cloud Computing Architecture and Enabling Technologies -- 2.4. Cloud Computing Deployment Models and Service Classes -- 2.4.1. Deployment Models -- 2.4.2. Service Classes -- 2.5. Introduction to the Firebase Cloud Platform -- 2.5.1. Firebase Cloud Database Configurations -- 2.5.2. Creating a Firebase Project and Real-time Database -- 2.5.3. Sending and Reading Data from the Database with an Android Application -- 2.6. Application Hosting on Firebase Using Node.js -- 2.6.1. Node.js Overview and Installation -- 2.6.2. Hosting a Web Application Using Node.js on Firebase for Reading and Writing Data to the Firebase Real-Time Database -- 2.7. Introduction to IBM Cloud Platform -- 2.7.1. IBM Cloud Database Configurations -- 2.7.2. Desktop Application to Send and Receive Data to the IBM Cloudant ; Database -- 2.7.3. Mobile Application to Send and Receive Data to the IBM Cloudant Database -- 2.8. Application Hosting on IBM Bluemix via the Eclipse IDE -- 2.8.1. Creating a Desktop Application to Send a Request to the CalculateArea servlet.; 2.8.2. Creating a Mobile Application to Send a Request to the CalculateArea Servlet -- References -- Chapter 3 -- Machine Learning Algorithms -- 3.1. Definition of AI, Machine Learning and Deep Learning -- 3.1.1. Artificial Narrow Intelligence (ANI) -- 3.1.2. Artificial General Intelligence (AGI) -- 3.1.3. Artificial Super Intelligence (ASI) -- 3.2. Overview of Machine Learning Algorithms -- 3.3. Unsupervised Learning Algorithms -- 3.3.1. Unsupervised Shallow Learning Models -- 3.3.1.1. K-Means Clustering -- 3.3.1.2. Hierarchical Clustering -- 3.3.1.3. Gaussian Mixture Models -- 3.3.2. Unsupervised Deep Learning Models -- 3.3.2.1. Restricted Boltzmann Machine (RBM) -- 3.4. Supervised Learning Algorithms -- 3.4.1. Supervised Shallow Learning Models -- 3.4.1.1. Simple Linear Regression -- 3.4.1.2. Multiple Linear Regression -- 3.4.1.3. Polynomial Regression -- 3.4.1.4. Naïve Bayes -- 3.4.1.5. K-Nearest Neighbour -- 3.4.2. Supervised Deep Learning Models -- 3.4.2.1. Multi-Layered Perceptrons -- 3.4.2.2. Convolutional Neural Network -- 3.5. Reinforcement Learning Algorithms -- 3.5.1. Q-Learning -- 3.5.2. SARSA -- 3.6. Ensemble Learning Algorithms -- 3.6.1. Random Forest -- 3.7. Deploying Javascript Machine Learning Algorithms on Firebase -- 3.7.1. Main Layout of the Application -- 3.7.2. Incorporating the KNN Flower Classification Link -- 3.7.3. Incorporating the Regression Algorithm Link -- 3.7.4. Incorporating the Clustering Algorithm Link -- References -- Chapter 4 -- Data Capture and Client Architecture for a Cloud-Based Real-Time Network Analytics System -- 4.1. Overview of Machine Learning Algorithms for Network Analytics -- 4.1.1. Classification of Network Data -- 4.1.2. Regression Analysis for Network Data -- 4.2. Complete System Model of the Network Analytics System -- 4.3. Mobile Application for Network Data Capture and Analytics.; 4.3.1. Creating the Android project -- 4.3.2. Adding Libraries -- 4.3.3. Android Application Layout -- 4.3.3.1. Visual Outlook on Final Application -- 4.3.3.2. Building the Visuals of activity_main.xml -- 4.3.3.3. Building the Visuals of Prediction.xml -- 4.3.3.4. Building the Visuals for csvdownload.xml -- 4.3.4. Declaring Global Variables in Main Activity -- 4.3.5. Retrieving the Last Index from the Cloud -- 4.3.6. Traffic Monitoring in the onCreate() Method -- 4.3.6.1. Initialising Components -- 4.3.6.2. Getting Initial Readings -- 4.3.6.3. Monitor Button -- 4.3.6.4. Stop Button -- 4.3.6.5. Go to Analysis Button -- 4.3.6.6. Go to Download Button -- 4.3.7. Getting Network Parameters -- 4.3.7.1. Getting Speed Data -- 4.3.7.2. Getting Packet Data -- 4.3.7.3. Getting Wi-Fi Data -- 4.3.8. Building the Main Thread -- 4.3.8.1. Creating a Thread with Runnable Class -- 4.3.8.2. Fetching Network Data -- 4.3.8.3. Updating UI and Live Monitor -- 4.3.8.4. Pushing Values to the Local Server -- 4.3.8.5. Pushing Values Directly to the Cloud -- 4.3.9. Live Graph Plotting -- 4.3.9.1. Initialising the Chart -- 4.3.9.2. Creating and Populating the Spinner -- 4.3.9.3. Applying the Adapter to the Spinner -- 4.3.9.4. Getting Spinner Value as a String -- 4.3.9.5. Programmatically Adding Data onto the Live Graph -- 4.3.10. Performing Analytics Using Cloud Servlet or Local Server -- 4.3.10.1. The "Predict" Button -- 4.3.10.2. The "Classify" Button -- 4.3.11. Downloading to .csv Files -- 4.3.11.1. Declaring Global Variables -- 4.3.11.2. Initialising Components in onCreate() -- 4.3.11.3. Browse Button -- 4.3.11.4. Download Last N Samples Button -- 4.3.11.5. Download by a Specific Date -- 4.3.11.6. Issuing the ; Directory Picker -- 4.3.11.7. Verifying Read and Write Permissions -- 4.3.11.8. Handling Permissions Request -- 4.3.11.9. Fetching Values from Cloudant Database.; 4.3.12. Setting Permissions in Manifest -- 4.3.13. Testing the Mobile application -- 4.3.13.1. Live Monitor -- 4.3.13.2. Downloading Functionalities -- 4.3.13.3. Performing Analytics -- 4.4. Desktop Application for Network Data Capture and Analytics -- 4.4.1. Creating the NetBeans project -- 4.4.2. Desktop Application Layout -- 4.4.2.1. Visual Outlook on Final Application -- 4.4.2.2. Adding a JFrame Form to the Project -- 4.4.2.3. Adding Components to JFrame -- 4.4.3. Renaming Components -- 4.4.4. Adding Libraries -- 4.4.5. Declaring Global Variables in Netmonitor.Java -- 4.4.6. Creating Live Monitor Layout -- 4.4.7. Retrieving the Last Index from the Cloud -- 4.4.8. Start Button -- 4.4.8.1. Retrieving the Number of Items -- 4.4.8.2. Finding Network Interface in Use -- 4.4.8.3. Getting Initial Parameters -- 4.4.8.4. Updating GUI and Live Monitor -- 4.8.4.5. Pushing Values to the Local Server -- 4.8.4.6. Pushing Values to the Cloud -- 4.4.9. Stop Button -- 4.4.10. Clearing Graph -- 4.4.11. Performing Analytics Using Servlet or Local Server -- 4.4.11.1. Predict Button -- 4.4.11.2. Classify Button -- 4.4.12. Downloading to .csv Files -- 4.4.12.1. Browse Button -- 4.4.12.2. Download Last N Samples Button -- 4.4.12.3. Download by Specific Date Button -- 4.4.12.4. Fetching Values from Cloudant Database -- 4.4.13. Testing the Desktop Application -- 4.4.13.1. Live Monitor -- 4.4.13.2. Downloading Functionalities -- 4.4.13.3. Performing Analytics -- 4.5. Cloud Database Configurations for Network Analytics -- 4.5.1. Creating a Cloudant Database to Store Network Data -- 4.5.2. Adding an Index to the Database -- References -- Chapter 5 -- Server and Servlet Architectures for a Cloud-Based Real-Time Network Analytics System -- 5.1. Local Server Implementation for Network Data Capture and Forecasting -- 5.1.1. Creating the NetBeans Project.; 5.1.2. Local Server Layout -- 5.1.2.1. Visual Outlook on Final Application -- 5.1.2.2. Adding Components to JFrame -- 5.1.3. Renaming Components -- 5.1.4. Adding Libraries -- 5.1.5. Declaring Global Variables in LocServer.java -- 5.1.6. Creating Live Monitor Layout -- 5.1.7. Retrieving the Last Index from the Cloud -- 5.1.8. Local Monitoring Server Implementation -- 5.1.8.1. Calling getNumberOfItems -- 5.1.8.2. Server Thread for Android Values -- 5.1.8.3. Server Thread for PC Values -- 5.1.8.4. Stopping the Server -- 5.1.8.5. Uploading Android Values to the Cloud -- 5.1.9. Filling Localhost Databases -- 5.1.10. Analytics -- 5.1.11. Classification -- 5.1.11.1. Filling Cloudant Databases -- 5.1.11.2. Retrieving Pre-Labelled Values from Cloudant Database or Localhost -- 5.1.11.3. Classifying Network Parameters Using K-Nearest Neighbour (KNN) -- 5.1.11.4. Performing K-Nearest Neighbour (KNN) -- 5.1.11.5. Classifying Network Parameters Using Multilayer Perceptron (MLP) -- 5.1.11.6. Performing Multilayer Perceptron (MLP) Classification -- 5.1.12. Regression -- 5.1.12.1. Using the Sliding Window Method -- 5.1.12.2. Filling Cloudant Databases -- 5.1.12.3. Retrieving Streaming Values from Cloudant Database -- 5.1.12.4. Multiple Linear Regression Models for Network data -- 5.1.12.5. Performing Multiple Linear Regression (MLR) -- 5.1.12.6. Multilayer Perceptron Models for Network data -- 5.1.12.7. Performing Multilayer Perceptron (MLP) Regression -- 5.1.13. Downloading to .csv Files -- 5.1.13.1. Browse Button -- 5.1.13.2. Download the Last N Samples Button -- 5.1.13.2. Download by Specific Date Button -- 5.1.14. Local Download and Analytics -- 5.1.15. Making the GUI User-Friendly -- 5.2. Testing the Local Server -- 5.2.1. Local Live Monitoring -- 5.2.2. Downloading ; Functionalities -- 5.2.3. Performing Analytics.; 5.3. Servlet Program for Network Analytics, Monitoring and Data Retrieval.
• Sommario/riassunto: With the emergence of revolutionary technological standards such as 5G and Industry 4.0, real time applications which require both cloud computing and machine learning are becoming increasingly common. Examples of such applications include real-time scheduling and resource allocation in cloud radio access networks, real-time process monitoring and control in industrial Internet of Things, network traffic analysis, short-term weather forecasting, and robotics. Given the increase in such applications, several cloud service providers such as Microsoft Azure Machine Learning, IBM Watson, and Google AI have started incorporating Artificial Intelligence (AI) applications on their platforms as well as providing Analytics as a Service. While it is now simple for users to deploy AI or machine learning algorithms using these cloud platforms, researchers from academia and industry can also develop their own machine learning applications and run them on these platforms to benefit from high processing power and global deploy ability. The main purpose of this book is to provide in-depth coverage of the programming methodologies and configurations required in developing real-time applications that require machine learning algorithms to be hosted on cloud computing platforms to leverage storage and computing resources. The real-time applications developed target network traffic analysis and weather forecasting systems. Several machine learning algorithms, namely multiple linear regression, K-Nearest-Neighbours, Multi-Layer-Perceptron, and Convolutional Neural Networks have been employed in the analysis. The programming languages used include Java, Javascript, HTML5 and MATLAB. Moreover, the Netbeans, Eclipse and Android studio IDEs have been used for developing desktop, web, and mobile apps as well as servlets. The use of several Application Programming Interfaces (APIs) to develop the desktop, mobile, and web apps have been fully elaborated. The main cloud platform used for the network analysis and weather forecasting systems is the IBM cloud, but Google Firebase, along with Node.js, have also been used in other examples of machine learning applications described in the book. In addition to hosting and running applications on the cloud, the setting up of local servers that can act as fog devices, using client-server sockets and network programming methodologies, has also been explained in detail. With detailed explanations on all fundamental concepts, programming techniques, and configuration steps in developing cloud hosted machine learning applications, this book will provide excellent guidance and a full hands-on experience to researchers, professionals and students working in this field.