INFORMATION TECHNOLOGY & BIOINFORMATICS INTERNATIONAL CONFERENCE ON ADVANCE IT, ENGINEERING AND MANAGEMENT SACAIM - 2023, VOLUME – 1


Book Description

Whiteflies pose a significant threat to agricultural productivity worldwide, causing damage to crops and economic losses. In this study, we present an Android-based whiteflies detection system utilizing deep learning techniques, specifically leveraging the YOLOv5 algorithm. The objective is to create a robust and efficient solution capable of real-time whitefly detection in agricultural fields. The proposed system capitalizes on the powerful capabilities of YOLOv5, a state-of-the-art object detection algorithm, known for its accuracy and speed.










Cognitive Informatics and Soft Computing


Book Description

The book presents new approaches and methods for solving real-world problems. It offers, in particular, exploratory research that describes novel approaches in the fields of Cognitive Informatics, Cognitive Computing, Computational Intelligence, Advanced Computing, Hybrid Intelligent Models and Applications. New algorithms and methods in a variety of fields are also presented, together with solution-based approaches. The topics addressed include various theoretical aspects and applications of Computer Science, Artificial Intelligence, Cybernetics, Automation Control Theory and Software Engineering.




ICCCE 2019


Book Description

This book is a collection research papers and articles from the 2nd International Conference on Communications and Cyber-Physical Engineering (ICCCE – 2019), held in Pune, India in Feb 2019. Discussing the latest developments in voice and data communication engineering, cyber-physical systems, network science, communication software, image- and multimedia processing research and applications, as well as communication technologies and other related technologies, it includes contributions from both academia and industry.




Learning with Kernels


Book Description

A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs—-kernels—for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different tasks and domains by the choice of the kernel function and the base algorithm. They are replacing neural networks in a variety of fields, including engineering, information retrieval, and bioinformatics. Learning with Kernels provides an introduction to SVMs and related kernel methods. Although the book begins with the basics, it also includes the latest research. It provides all of the concepts necessary to enable a reader equipped with some basic mathematical knowledge to enter the world of machine learning using theoretically well-founded yet easy-to-use kernel algorithms and to understand and apply the powerful algorithms that have been developed over the last few years.




Healthcare Systems and Health Informatics


Book Description

This book covers the fundamentals of IoT and healthcare systems for carrying out system architectures, protocols, wearable devices, and interoperability. It explores major challenges in artificial intelligence (AI) and smart computing in resource-constrained IoT-based applications along with cost, energy efficiency, and the availability of quality service. Healthcare Systems and Health Informatics: Using Internet of Things explores the role of AI and smart computing in health informatics and healthcare with an emphasis on clinical data management and analysis for precise prediction and prompt action. It presents cutting-edge tracking, monitoring, real-time assistance, and security for IoT in healthcare and broadly discusses wearable sensors and IoT devices and their role in smart living assistance. The book goes on to describe a system model and architecture for a clear picture of energy conservation–based IoT in healthcare and explains the challenges and opportunities with IoT-based healthcare industries. A study of the threats and impacts, along with the need for information security, is also included. The chapters are written by experts in the field, and this book provides a comprehensive description of the important aspects of IoT and health from a beginner- to advanced-level perspective and is ideal for researchers, academicians, students, persons in industry, technologists, and entrepreneurs.




Social Big Data Analytics


Book Description

This book focuses on data and how modern business firms use social data, specifically Online Social Networks (OSNs) incorporated as part of the infrastructure for a number of emerging applications such as personalized recommendation systems, opinion analysis, expertise retrieval, and computational advertising. This book identifies how in such applications, social data offers a plethora of benefits to enhance the decision making process. This book highlights that business intelligence applications are more focused on structured data; however, in order to understand and analyse the social big data, there is a need to aggregate data from various sources and to present it in a plausible format. Big Social Data (BSD) exhibit all the typical properties of big data: wide physical distribution, diversity of formats, non-standard data models, independently-managed and heterogeneous semantics but even further valuable with marketing opportunities. The book provides a review of the current state-of-the-art approaches for big social data analytics as well as to present dissimilar methods to infer value from social data. The book further examines several areas of research that benefits from the propagation of the social data. In particular, the book presents various technical approaches that produce data analytics capable of handling big data features and effective in filtering out unsolicited data and inferring a value. These approaches comprise advanced technical solutions able to capture huge amounts of generated data, scrutinise the collected data to eliminate unwanted data, measure the quality of the inferred data, and transform the amended data for further data analysis. Furthermore, the book presents solutions to derive knowledge and sentiments from BSD and to provide social data classification and prediction. The approaches in this book also incorporate several technologies such as semantic discovery, sentiment analysis, affective computing and machine learning. This book has additional special feature enriched with numerous illustrations such as tables, graphs and charts incorporating advanced visualisation tools in accessible an attractive display.




Body Sensor Networks


Book Description

The last decade has witnessed a rapid surge of interest in new sensing and monitoring devices for wellbeing and healthcare. One key development in this area is wireless, wearable and implantable in vivo monitoring and intervention. A myriad of platforms are now available from both academic institutions and commercial organisations. They permit the management of patients with both acute and chronic symptoms, including diabetes, cardiovascular diseases, treatment of epilepsy and other debilitating neurological disorders. Despite extensive developments in sensing technologies, there are significant research issues related to system integration, sensor miniaturisation, low-power sensor interface, wireless telemetry and signal processing. In the 2nd edition of this popular and authoritative reference on Body Sensor Networks (BSN), major topics related to the latest technological developments and potential clinical applications are discussed, with contents covering. Biosensor Design, Interfacing and Nanotechnology Wireless Communication and Network Topologies Communication Protocols and Standards Energy Harvesting and Power Delivery Ultra-low Power Bio-inspired Processing Multi-sensor Fusion and Context Aware Sensing Autonomic Sensing Wearable, Ingestible Sensor Integration and Exemplar Applications System Integration and Wireless Sensor Microsystems The book also provides a comprehensive review of the current wireless sensor development platforms and a step-by-step guide to developing your own BSN applications through the use of the BSN development kit.




Sentiment Analysis and Opinion Mining


Book Description

Sentiment analysis and opinion mining is the field of study that analyzes people's opinions, sentiments, evaluations, attitudes, and emotions from written language. It is one of the most active research areas in natural language processing and is also widely studied in data mining, Web mining, and text mining. In fact, this research has spread outside of computer science to the management sciences and social sciences due to its importance to business and society as a whole. The growing importance of sentiment analysis coincides with the growth of social media such as reviews, forum discussions, blogs, micro-blogs, Twitter, and social networks. For the first time in human history, we now have a huge volume of opinionated data recorded in digital form for analysis. Sentiment analysis systems are being applied in almost every business and social domain because opinions are central to almost all human activities and are key influencers of our behaviors. Our beliefs and perceptions of reality, and the choices we make, are largely conditioned on how others see and evaluate the world. For this reason, when we need to make a decision we often seek out the opinions of others. This is true not only for individuals but also for organizations. This book is a comprehensive introductory and survey text. It covers all important topics and the latest developments in the field with over 400 references. It is suitable for students, researchers and practitioners who are interested in social media analysis in general and sentiment analysis in particular. Lecturers can readily use it in class for courses on natural language processing, social media analysis, text mining, and data mining. Lecture slides are also available online. Table of Contents: Preface / Sentiment Analysis: A Fascinating Problem / The Problem of Sentiment Analysis / Document Sentiment Classification / Sentence Subjectivity and Sentiment Classification / Aspect-Based Sentiment Analysis / Sentiment Lexicon Generation / Opinion Summarization / Analysis of Comparative Opinions / Opinion Search and Retrieval / Opinion Spam Detection / Quality of Reviews / Concluding Remarks / Bibliography / Author Biography