“…As you progress, you'll cover the SAP Intelligent RPA factory, Desktop Studio, Cloud Studio, and the Bot store. You'll also learn about the building blocks of the SAP Intelligent RPA solution and creating bots from initial application declaration to workflow design and deployment, along with making bots run in attended and unattended modes. …”

Tabla de Contenidos: “…Chapter 11 Eye-Based Cursor Control and Eye Coding Using Hog Algorithm and Neural Network -- 11.1 Introduction -- 11.2 Related Work -- 11.3 Methodology -- 11.3.1 Eye Blink Detection -- 11.3.2 Hog Algorithm -- 11.3.3 Eye Gaze Detection -- 11.3.3.1 Deep Learning and CNN -- 11.3.3.2 Hog Algorithm for Gaze Determination -- 11.3.4 GUI Automation -- 11.4 Experimental Analysis -- 11.4.1 Eye-Based Cursor Control -- 11.4.2 Eye Coding -- 11.5 Observation and Results -- 11.6 Conclusion -- 11.7 Future Scope -- References -- Chapter 12 Role of Artificial Intelligence in the Agricultural System -- 12.1 Introduction -- 12.2 Artificial Intelligence Effect on Farming -- 12.2.1 Agriculture Lifecycle -- 12.2.2 Problems with Traditional Methods of Farming -- 12.3 Applications of Artificial Intelligence in Agriculture -- 12.3.1 Forecasting Weather Details -- 12.3.2 Crop and Soil Quality Surveillance -- 12.3.3 Pesticide Use Reduction -- 12.3.4 AI Farming Bots -- 12.3.5 AI-Based Monitoring Systems -- 12.3.6 AI-Based Irrigation System -- 12.4 Robots in Agriculture -- 12.5 Drones for Agriculture -- 12.6 Advantage of AI Implementation in Farming -- 12.6.1 Intelligent Agriculture Cloud Platform -- 12.6.1.1 Remote Control and Administration in Real Time -- 12.6.1.2 Consultation of Remote Experts -- 12.7 Research, Challenges, and Scope for the Future -- 12.8 Conclusion -- References -- Chapter 13 Improving Wireless Sensor Networks Effectiveness with Artificial Intelligence -- 13.1 Introduction -- 13.2 Wireless Sensor Network (WSNs) -- 13.3 AI and Multi-Agent Systems -- 13.4 WSN and AI -- 13.5 Multi-Agent Constructed Simulation -- 13.6 Multi-Agent Model Plan -- 13.7 Simulation Models on Behalf of Wireless Sensor Network -- 13.8 Model Plan -- 13.8.1 Hardware Layer -- 13.8.2 Middle Layer -- 13.8.3 Application Layer -- 13.9 Conclusion -- References -- Index -- EULA…”

Tabla de Contenidos: “…7.3.1 Detection and Collection of Data -- 7.3.2 Initial Processing of Collected Data -- 7.3.3 Modeling as Per Requirement -- 7.3.4 Influential Parameters -- 7.3.5 Identification of Best Working Path -- 7.3.6 Modifying Output With Respect Sensed Input -- 7.4 Economics of PdM -- 7.5 PdM for Production and Product -- 7.6 Implementation of IPdM -- 7.6.1 Manufacturing with Zero Defects -- 7.6.2 Sense of the Windsene INDSENSE -- 7.7 Case Studies -- 7.7.1 Area 1-Heavy Ash Evacuation -- 7.7.2 Area 2-Seawater Pumps -- 7.7.3 Evaporators -- 7.7.4 System Deployment Considerations in General -- 7.8 Automotive Industry-Integrated IoT -- 7.8.1 Navigation Aspect -- 7.8.2 Continual Working of Toll Booth -- 7.8.3 Theft Security System -- 7.8.4 Black Box-Enabled IoT -- 7.8.5 Regularizing Motion of Emergency Vehicle -- 7.8.6 Pollution Monitoring System -- 7.8.7 Timely Assessment of Driver's Condition -- 7.8.8 Vehicle Performance Monitoring -- 7.9 Conclusion -- References -- Chapter 8 Role of IoT in Product Development -- 8.1 Introduction -- 8.1.1 Industry 4.0 -- 8.2 Need to Understand the Product Architecture -- 8.3 Product Development Process -- 8.3.1 Criteria to Classify the New Products -- 8.3.2 Product Configuration -- 8.3.3 Challenges in Product Development while Developing IoT Products (Data-Driven Product Development) -- 8.3.4 Role of IoT in Product Development for Industrial Applications -- 8.3.5 Impacts and Future Perspectives of IoT in Product Development -- 8.4 Conclusion -- References -- Chapter 9 Benefits of IoT in Automated Systems -- 9.1 Introduction -- 9.2 Benefits of Automation -- 9.2.1 Improved Productivity -- 9.2.2 Efficient Operation Management -- 9.2.3 Better Use of Resources -- 9.2.4 Cost-Effective Operation -- 9.2.5 Improved Work Safety -- 9.2.6 Software Bots -- 9.2.7 Enhanced Public Sector Operations -- 9.2.8 Healthcare Benefits…”

Tabla de Contenidos: “…. -- 6.1 Introduction -- 6.2 Related works -- 6.3 Proposed model -- 6.3.1 Tokenization -- 6.3.2 Stop words removal -- 6.3.3 Normalization -- 6.3.4 Feature extraction -- 6.3.4.1 CountVectorizer -- 6.3.4.2 Term frequency and inverse document frequency -- 6.3.4.3 Word2vec -- 6.3.4.4 Improved adaptive synthetic sampling (ADASYN) -- 6.4 Results and discussion -- 6.5 Conclusion -- References -- 7 Emotion detection from text data using machine learning for human behavior analysis -- 7.1 Introduction -- 7.1.1 Human behavior analysis -- 7.1.1.1 Theories of emotion -- 7.1.1.1.1 Social cognitive theory -- 7.1.1.2 Theories of personality -- 7.1.1.2.1 Social identity theory -- 7.1.1.2.2 Self-determination theory -- 7.1.2 Models of emotion -- 7.1.3 Affective computing for emotion detection -- 7.1.4 Natural language processing for emotion detection -- 7.1.4.1 Applications -- 7.1.4.2 Challenges -- 7.2 Available tools and resources -- 7.2.1 Tools for emotion detection -- 7.2.2 Datasets -- 7.2.3 Feature extraction tools -- 7.3 Methods and materials -- 7.3.1 Rule-based approaches -- 7.3.1.1 Lexicon-based approach -- 7.3.1.2 Keyword-based approach -- 7.3.1.3 Regular expressions -- 7.3.2 Statistical learning -- 7.3.2.1 Machine learning-based approaches -- 7.3.2.2 Deep learning methods -- 7.3.2.3 Contextual adaptation -- 7.3.2.4 Personalized bots -- 7.3.3 Explainable AI for emotion detection -- 7.4 Outlook -- 7.4.1 Ethical considerations -- 7.4.2 Limitations of NLP in emotion detection -- 7.5 Conclusion -- References -- 8 Optimization of effectual sentiment analysis in film reviews using machine learning techniques -- 8.1 Introduction -- 8.2 Literature Survey -- 8.3 Proposed System -- 8.3.1 Hybrid algorithm Design -- 8.3.2 Solution Representation…”

Tabla de Contenidos: “…7.3.1 Detection and Collection of Data -- 7.3.2 Initial Processing of Collected Data -- 7.3.3 Modeling as Per Requirement -- 7.3.4 Influential Parameters -- 7.3.5 Identification of Best Working Path -- 7.3.6 Modifying Output With Respect Sensed Input -- 7.4 Economics of PdM -- 7.5 PdM for Production and Product -- 7.6 Implementation of IPdM -- 7.6.1 Manufacturing with Zero Defects -- 7.6.2 Sense of the Windsene INDSENSE -- 7.7 Case Studies -- 7.7.1 Area 1-Heavy Ash Evacuation -- 7.7.2 Area 2-Seawater Pumps -- 7.7.3 Evaporators -- 7.7.4 System Deployment Considerations in General -- 7.8 Automotive Industry-Integrated IoT -- 7.8.1 Navigation Aspect -- 7.8.2 Continual Working of Toll Booth -- 7.8.3 Theft Security System -- 7.8.4 Black Box-Enabled IoT -- 7.8.5 Regularizing Motion of Emergency Vehicle -- 7.8.6 Pollution Monitoring System -- 7.8.7 Timely Assessment of Driver's Condition -- 7.8.8 Vehicle Performance Monitoring -- 7.9 Conclusion -- References -- Chapter 8 Role of IoT in Product Development -- 8.1 Introduction -- 8.1.1 Industry 4.0 -- 8.2 Need to Understand the Product Architecture -- 8.3 Product Development Process -- 8.3.1 Criteria to Classify the New Products -- 8.3.2 Product Configuration -- 8.3.3 Challenges in Product Development while Developing IoT Products (Data-Driven Product Development) -- 8.3.4 Role of IoT in Product Development for Industrial Applications -- 8.3.5 Impacts and Future Perspectives of IoT in Product Development -- 8.4 Conclusion -- References -- Chapter 9 Benefits of IoT in Automated Systems -- 9.1 Introduction -- 9.2 Benefits of Automation -- 9.2.1 Improved Productivity -- 9.2.2 Efficient Operation Management -- 9.2.3 Better Use of Resources -- 9.2.4 Cost-Effective Operation -- 9.2.5 Improved Work Safety -- 9.2.6 Software Bots -- 9.2.7 Enhanced Public Sector Operations -- 9.2.8 Healthcare Benefits…”

Tabla de Contenidos: “…10.9.1 Confusion Matrix -- 10.9.2 Gaussian Naïve Bayes -- 10.9.3 Decision Tree Classifier -- 10.9.4 Karnough Nearest Neighbor Classifier -- 10.9.5 Neural Network -- 10.9.6 Accuracy Scores -- 10.10 Conclusion and Future Work -- References -- 11 Big Data, Artificial Intelligence and Machine Learning: A Paradigm Shift in Election Campaigns -- 11.1 Introduction -- 11.2 Big Data Reveals the Voters' Preference -- 11.2.1 Use of Software Applications in Election Campaigns -- 11.2.1.1 Team Joe App -- 11.2.1.2 Trump 2020 -- 11.2.1.3 Modi App -- 11.3 Deep Fakes and Election Campaigns -- 11.3.1 Deep Fake in Delhi Elections -- 11.4 Social Media Bots -- 11.5 Future of Artificial Intelligence and Machine Learning in Election Campaigns -- References -- 12 Impact of Optimized Segment Routing in Software Defined Networks -- 12.1 Introduction -- 12.2 Software-Defined Network -- 12.3 SDN Architecture -- 12.4 Segment Routing -- 12.5 Segment Routing in SDN -- 12.6 Traffic Engineering in SDN -- 12.7 Segment Routing Protocol -- 12.8 Simulation and Result -- 12.9 Conclusion and Future Work -- References -- 13 An Investigation into COVID-19 Pandemic in India -- 13.1 Introduction -- 13.1.1 Symptoms of COVID-19 -- 13.1.2 Precautionary Measures -- 13.1.3 Ways of Spreading the Coronavirus -- 13.2 Literature Survey -- 13.3 Technologies Used to Fight COVID-19 -- 13.3.1 Robots -- 13.3.2 Drone Technology -- 13.3.3 Crowd Surveillance -- 13.3.4 Spraying the Disinfectant -- 13.3.5 Sanitizing the Contaminated Areas -- 13.3.6 Monitoring Temperature Using Thermal Camera -- 13.3.7 Delivering Essential Things -- 13.3.8 Public Announcement in the Infected Areas -- 13.4 Impact of COVID-19 on Business -- 13.4.1 Impact on Financial Markets -- 13.4.2 Impact on Supply Side -- 13.4.3 Impact on Demand Side -- 13.4.4 Impact on International Trade -- 13.5 Impact of COVID-19 on Indian Economy…”

Tabla de Contenidos: “…4.9 Verwendung von Stockfotos, -videos und -icons -- 4.10 Content Planung‌ -- 4.10.1 Redaktionsplanung mit Tools -- 4.10.2 Beiträge vorausplanen -- 4.10.3 Content Erstellung aus Long-Form-Content -- 4.10.4 Content Recycling‌ -- Kapitel 5: Aufbau einer Community auf Instagram -- 5.1 Eigene Webpräsenzen -- 5.2 Soziale Netzwerke -- 5.3 Community Management -- 5.3.1 Kommentieren -- 5.3.2 Anderen Nutzern folgen -- 5.3.3 »Gefällt mir«-Angaben -- 5.3.4 Fragen beantworten‌ -- 5.3.5 Bleiben Sie sich selbst treu -- 5.3.6 Suche passender Profile und Beiträge über Hashtags -- 5.3.7 Standorte -- 5.3.8 Interaktionen fördern -- 5.3.9 Tool-Tipp Hootsuite -- 5.4 Fan-Communities -- 5.5 Challenges -- 5.6 Shoutouts -- 5.7 Werbung auf Instagram schalten -- 5.8 Influencer-Generated-Content‌ -- 5.9 InstaMeets -- 5.9.1 Instagramers -- 5.9.2 Weltweite InstaMeets -- 5.9.3 Persönliche Treffen und Freundschaften -- 5.10 Community-Regeln -- 5.10.1 Eigene Fotos und Videos posten -- 5.10.2 Fotos anderer Instagrammer bearbeiten und teilen -- 5.10.3 Authentizität, Humor und Menschlichkeit -- 5.10.4 Nutzer blockieren und Inhalte melden -- 5.11 Gewinnspiele -- 5.12 Unseriöse Methoden zum Follower-Aufbau -- 5.12.1 Follower- und Like-Apps -- 5.12.2 Like-Bots -- 5.12.3 Follower kaufen -- 5.12.4 Instagram Pods -- Kapitel 6: Influencer-Marketing -- 6.1 Relevanz von Influencer-Marketing auf Instagram -- 6.1.1 Sichtbarkeit und Relevanz in der Aufmerksamkeitsökonomie -- 6.1.2 Umgehen von realen (und mentalen) AdBlockern -- 6.1.3 Zugang zu relevanten Zielgruppen -- 6.1.4 Relevante Reichweite -- 6.1.5 Glaubwürdigkeit, Authentizität und Vertrauen -- 6.1.6 Kunden mit einem höheren Lifetime Value -- 6.1.7 Content-Kreation -- 6.1.8 Medien- und Storytelling-Kompetenz -- 6.1.9 Differenzierung zum Wettbewerb -- 6.1.10 Langlebige Partnerschaften mit großem Potenzial…”

Tabla de Contenidos: “…. -- 13.1 Introduction -- 13.2 Literature survey -- 13.3 Methodology -- 13.3.1 Distinguishing midlife crisis symptoms -- 13.3.2 Designing of the prediction model -- 13.3.3 Application of LDA and statistical comparison -- 13.3.3.1 Formulation of Dirichlet distribution -- 13.3.3.2 Categorization in Bayesian model -- 13.3.3.3 Concept of topic modeling -- 13.4 Result and discussion -- 13.5 Conclusion and future scope -- References -- 14 Autonomous robotic system for ultraviolet disinfection -- 14.1 Introduction -- 14.2 Background -- 14.2.1 Ultraviolet light for disinfection -- 14.2.2 Exposure time for deactivation of the bacteria -- 14.2.3 Flow chart of UV bot control logic -- 14.2.4 Calculations related to the time for disinfection -- 14.3 Implementation -- 14.4 Model topology -- 14.4.1 UV-C light robotic vehicle -- 14.5 Conclusion -- References -- 15 Emerging health start-ups for economic feasibility: opportunities during COVID-19 -- 15.1 Introduction -- 15.2 Health-tech verticals for start-ups…”

“…This collection of articles from MIT Sloan Management Review examines the ways executives can increase their influence by sharing their power and listening more, manage the data and bots that are managing their businesses, and use Twitter and social media to shape the conversation about their companies."…”

“…Rather than click through page after endless page, why not let bots do the work for you? Webbots, Spiders, and Screen Scrapers will show you how to create simple programs with PHP/CURL to mine, parse, and archive online data to help you make informed decisions…”

“…Today it’s sexy again, and that far-off future of intelligent bots is just around the corner. Consider the latest trend, AI-as-a-Service (AIaaS). …”

“…With this 75-page report, you’ll learn how your team can query information, work together on solutions, enter commands with bots and scripts, and comment on the work—all in one place and in real time. …”

“…Dissect forms of infections including viruses, worms, bots, and Trojans; and encryption with RSA algorithm as the working example…”

“…Digital Information Ecosystems: Smart Press crosses academic knowledge with research by media groups to understand this evolution and analyze the future of the sector, including the imminent employment of bots and artificial intelligence. The book adopts an original and multidisciplinary approach to this topic: combining the science of media economics with the experience of a practicing journalist of a major daily newspaper. …”

“…You'll also find features on an ancient and unusual maker material, and an excerpt from Encyclopedia of Electronic Components, a follow-up title to Charles Platt's best-selling book Make: Electronics.You'll get great projects like CoffeeBots (Arduino-controlled coffee can robots), GlueMotor (control your own robots with an iPhone app), AudioBooks (amplified speakers that look like hardbound books), and KAPstan (a kite winch that makes winding kite line a breeze)…”

“…With this book, you'll be able to tackle some of today's real world big data, smart bots, and other complex data problems. You’ll see how deep learning is a complex and more intelligent aspect of machine learning for modern smart data analysis and usage. …”

“…Build your own teams to enhance collaboration Use team channels to bring structure and relevance to your work Work smarter with apps, tabs, extensions, connectors, and bots Create, upload, edit, and share Microsoft 365 documents inside Teams Stay connected via chat and video calls Get more done in every Teams meeting Customize Teams to maximize personal and organizational efficiency Look up just the tasks and lessons you need…”