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This book presents an overview of the components, approaches and techniques which are used to build a mobile phoneapplication that uses short messaging service (SMS) text messages to improve interaction, information distribution and communication of stakeholders in a university setting. The proposed application is built upon a multiple compatible mobile phone menu-based subscription management application that is also customizable. Since SMS has the potential to fill significantconnectivity and service gaps, this application can provide support for them to become more ubiquitous. Event-based approach towards context-aware personalized notification service is adopted, i.e. user will receive relevant immediate SMS to his/her mobile phone based on his/her subscription for preferred notifications. A trigger enables event management system to send out (semi-) automated personalized notification. Notification services that understand the context within which their users operate, i.e. identity,activity and time are derived based on a set of predetermined rules. This will benefit the stakeholders in terms of getting up-to-date notifications.
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.
Provides research developments on mobile technologies and services. Explains how users of such applications access intelligent and adaptable information services, maximizing convenience and minimizing intrusion.
Alarm or alert detection remains an issue in various areas from nature, i.e. flooding, animals or earthquake, to software systems. Liveness, dynamicity, reactivity of alarm systems: how to ensure the warning information reach the right destination at the right moment and in the right location, still being relevant for the recipient, in spite of the various and successive filters of confidentiality, privacy, firewall policies, etc.? Also relevant in this context are to technical contingency issues: material failure, defect of connection, break of channels, independence of information routes and sources? Alarms with crowd media, (mis)information vs. rumours: how to make the distinction? The prediction of natural disasters (floods, avalanches, etc.), health surveillance (affectionate fevers of cattle, pollution by pesticides, etc.), air, sea and land transport, or space surveillance to prevent Risks of collisions between orbital objects involve more and more actors within Information Systems, one of whose purposes is the dissemination of alerts. By expanding the capabilities and functionality of such national or international systems, social networks are playing a growing role in dissemination and sharing, eg. with the support of systems like the Google Alert (https://www.google.fr/alerts) which concerns the publication of contents online. Recently, the Twitter microblogging platform announced a broadcast service, designed to help government organizations with alerts to the public. The proper functioning of such systems depends on fundamental properties such as resilience, liveliness and responsiveness: any alert must absolutely reach the right recipient at the right time and in the right place, while remaining relevant to him, despite the various constraints. on the one hand to external events, such as hardware failures, connection faults, breaks in communication channels, on the other hand to confidentiality, such as the collection and use of personal data (with or without the consent of the user), or the disparity of access policies (generation according to industrial, technological, security constraints, management of internal / external policies, etc.) between actors. This book opens the discussion on the "procrastination", the dynamics and the reactivity of the alert systems, but also the problems of confidentiality, filtering of information, and the means of distinguishing information and rumor. - Presents alarm or alert detection in all its aspects - Finds a solution so that the alert information reaches the right destination - Find relevance to various technical issues
Summary Machine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. About the Book A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interestingor useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful. Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book. What's Inside A no-nonsense introduction Examples showing common ML tasks Everyday data analysis Implementing classic algorithms like Apriori and Adaboos Table of Contents PART 1 CLASSIFICATION Machine learning basics Classifying with k-Nearest Neighbors Splitting datasets one feature at a time: decision trees Classifying with probability theory: naïve Bayes Logistic regression Support vector machines Improving classification with the AdaBoost meta algorithm PART 2 FORECASTING NUMERIC VALUES WITH REGRESSION Predicting numeric values: regression Tree-based regression PART 3 UNSUPERVISED LEARNING Grouping unlabeled items using k-means clustering Association analysis with the Apriori algorithm Efficiently finding frequent itemsets with FP-growth PART 4 ADDITIONAL TOOLS Using principal component analysis to simplify data Simplifying data with the singular value decomposition Big data and MapReduce
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This book focuses on the techniques of artificial intelligence that are mainly used in the power electronics field for the optimization of lost vehicle power. With the intention of optimizing the powerful energy of the vehicles and producing reliable energy, the most efficient methods, algorithms, and strategies of ethical artificial intelligence (AI) are being applied. By employing machine learning methods, the optimization of power energy in vehicles can be quickly recovered and managed efficiently. In today’s bustling world, power energy is indispensable for progress, yet in congested Vehicular Ad-hoc Networks (VANETs), vehicles often face power depletion and decreased efficiency. This book explores these challenges, encompassing not only power but also other critical power electronics within vehicles. We aim to introduce innovative approaches, leveraging ethical AI methods, to optimize energy performance in the face of these difficulties. Through this exploration, we seek to provide practical insights into navigating congested VANET environments while upholding ethical principles in technological advancements. Our book will discuss the current power energy concerns faced by vehicles and also contribute a novel strategy to overcome those concerns. The employment of ethical AI in vehicular power energy will undoubtedly improve the effectiveness and production of vehicles.
Internet-based information systems, the second covering the large-scale in- gration of heterogeneous computing systems and data resources with the aim of providing a global computing space. Eachofthesefourconferencesencouragesresearcherstotreattheirrespective topics within a framework that incorporates jointly (a) theory, (b) conceptual design and development, and (c) applications, in particular case studies and industrial solutions. Following and expanding the model created in 2003, we again solicited and selected quality workshop proposals to complement the more “archival” nature of the main conferences with research results in a number of selected and more “avant-garde” areas related to the general topic of Web-based distributed c- puting. For instance, the so-called Semantic Web has given rise to several novel research areas combining linguistics, information systems technology, and ar- ?cial intelligence, such as the modeling of (legal) regulatory systems and the ubiquitous nature of their usage. We were glad to see that ten of our earlier s- cessful workshops (ADI, CAMS, EI2N, SWWS, ORM, OnToContent, MONET, SEMELS, COMBEK, IWSSA) re-appeared in 2008 with a second, third or even ?fth edition, sometimes by alliance with other newly emerging workshops, and that no fewer than three brand-new independent workshops could be selected from proposals and hosted: ISDE, ODIS and Beyond SAWSDL. Workshop - diences productively mingled with each other and with those of the main c- ferences, and there was considerable overlap in authors.
This book includes high-quality research papers presented at the Fourth International Conference on Innovative Computing and Communication (ICICC 2021), which is held at the Shaheed Sukhdev College of Business Studies, University of Delhi, Delhi, India, on February 20–21, 2021. Introducing the innovative works of scientists, professors, research scholars, students and industrial experts in the field of computing and communication, the book promotes the transformation of fundamental research into institutional and industrialized research and the conversion of applied exploration into real-time applications.