Data collection allows today’s businesses to cater to each customer’s individual needs and provides a necessary edge in a competitive market. However, any breach in confidentiality can cause serious consequences for both the consumer and the company.The Handbook of Research on Emerging Developments in Data Privacy brings together new ideas on how to deal with potential leaks of valuable customer information. Highlighting the legal aspects of identity protection, trust and security, and detection techniques, this comprehensive work is a valuable resource for any business, legal, or technology professional looking to improve information security within their organization.
Discover the potential of India's growing market with this practical guide for NRIs and foreign entrepreneurs. It offers clear strategies for navigating complex regulations, leveraging tax incentives, and managing approval processes. Designed to empower readers, this book provides the knowledge needed to seize opportunities and succeed in India's dynamic economy, contributing to its ambitious growth goals. With over 11 years of experience in India entry strategies and tax compliance, CA Manish Gupta has helped more than 300 global companies from 15+ countries navigate the complexities of the Indian market. As the founder of Manish Anil Gupta & Co. and an author of 150+ blogs, he is on a mission to help business owners and NRIs navigate the complexities of Indian taxation and compliance.
The rapid evolution of large language models (LLMs) has led to the next major frontier: the AI agents. AI agents are software programs that leverage AI to learn, adapt, and perform tasks autonomously on behalf of users or other systems. Today, AI agents are transforming industries, increasing efficiency, and increasing innovation across business domains. This book provides practical steps for designing and building AI systems that deliver true intelligent automation. This book offers a comprehensive and practical guide to building effective AI agents for real-world LLM applications. It covers all essential topics: from the basics of AI, ML, and GenAI to agent architectures, core components, and design principles. Advanced concepts such as agentic AI frameworks, agentic design patterns, and multi-agent collaboration are also covered. The book also provides the best practices and step-by-step guides for implementing AI agents at scale. Business professionals will benefit from detailed case studies and applications in finance, healthcare, and e-commerce that demonstrate how AI agents are being applied across industries. This book further highlights key implementation challenges along with mitigation strategies related to deployment, building trust, and adoption of AI agents. By the end of this book, readers will be equipped to confidently design, build, and deploy robust, ethical, and scalable AI agents, acquiring industry-ready skills for the future of AI-driven automation. WHAT YOU WILL LEARN ● Understand AI agent fundamentals, workflows, and ML basics. ● Explore agentic AI frameworks and design principles. ● Learn core components with modern agentic design patterns. ● Master multi-agent system architectures and collaboration. ● Build autonomous AI agents with safety. ● Learn practical implementation of designing, deploying, and optimizing AI agents. WHO THIS BOOK IS FOR This book is for AI practitioners, developers, and business leaders seeking to design, build, and deploy effective AI agents for real-world applications. It is also useful for business leaders aiming to leverage AI agents to drive efficiency and gain a competitive advantage, along with tech enthusiasts interested in understanding how AI agents are revolutionizing business transformation and future trends.
Information retrieval with verbose natural language queries has been generating a lot of interest in recent years. The focus of many novel search applications has shifted from short keyword queries to verbose queries. Examples include question answering systems and dialogue systems, voice search on mobile devices, and entity search engines like Facebook's Graph Search or Google's Knowledge Graph. However, the performance of textbook information retrieval techniques for such verbose queries is not as good as that for their shorter counterparts. Thus, effective handling of verbose queries has become a critical factor for adoption of information retrieval techniques in this new breed of search applications.Over the past decade, the information retrieval community has deeply explored the problem of transforming natural language verbose queries using operations like reduction, weighting, expansion, reformulation and segmentation into more effective structural representations.This is the first monograph to provide a coherent and organized survey on this topic. It puts together the various research pieces of the puzzle, provides a comprehensive and structured overview of diverse proposed methods, and lists several application scenarios where effective verbose query processing can make a significant difference.Information Retrieval with Verbose Queries is a very timely reference on this important topic. It is entirely based on previously published research and publicly available datasets and as such, it should prove useful for both practitioners and academic researchers interested in reproducing the reported results.
Outlier (or anomaly) detection is a very broad field which has been studied in the context of a large number of research areas like statistics, data mining, sensor networks, environmental science, distributed systems, spatio-temporal mining, etc. Initial research in outlier detection focused on time series-based outliers (in statistics). Since then, outlier detection has been studied on a large variety of data types including high-dimensional data, uncertain data, stream data, network data, time series data, spatial data, and spatio-temporal data. While there have been many tutorials and surveys for general outlier detection, we focus on outlier detection for temporal data in this book. A large number of applications generate temporal datasets. For example, in our everyday life, various kinds of records like credit, personnel, financial, judicial, medical, etc., are all temporal. This stresses the need for an organized and detailed study of outliers with respect to such temporal data.In the past decade, there has been a lot of research on various forms of temporal data including consecutive data snapshots, series of data snapshots and data streams. Besides the initial work on time series, researchers have focused on rich forms of data including multiple data streams, spatio-temporal data, network data, community distribution data, etc. Compared to general outlier detection, techniques for temporal outlier detection are very different. In this book, we will present an organized picture of both recent and past research in temporal outlier detection. We start with the basics and then ramp up the reader to the main ideas in state-of-the-art outlier detection techniques. We motivate the importance of temporal outlier detection and brief the challenges beyond usual outlier detection. Then, we list down a taxonomy of proposed techniques for temporal outlier detection. Such techniques broadly include statistical techniques (like AR models, Markov models, histograms, neuralnetworks), distance- and density-based approaches, grouping-based approaches (clustering, community detection), network-based approaches, and spatio-temporal outlier detection approaches. We summarize by presenting a wide collection of applications where temporal outlier detection techniques have been applied to discover interesting outliers. Table of Contents: Preface / Acknowledgments / Figure Credits / Introduction and Challenges / Outlier Detection for Time Series and Data Sequences / Outlier Detection for Data Streams / Outlier Detection for Distributed Data Streams / Outlier Detection for Spatio-Temporal Data / Outlier Detection for Temporal Network Data / Applications of Outlier Detection for Temporal Data / Conclusions and Research Directions / Bibliography / Authors' Biographies
Der Einsatz von Handwerkzeugen wird in der Industrie auf verschiedenen Ebenen immer noch sehr gesch tzt. Die Anwendung von Handwerkzeugen variiert von einfachen Aufgaben wie H mmern bis hin zu komplizierten, komplexen und pr zisionsfordernden Aufgaben wie die von chirurgischen Skalpellen. Wenn ein Benutzer wiederholt und kontinuierlich mit einem ungeeigneten Werkzeuggriff arbeitet, kann er an einer kumulativen Traumaerkrankung (CTD) leiden, daher ist es sehr wichtig, den Werkzeuggriff so zu gestalten, dass er aus Sicht des Benutzers komfortabel ist. Das Ziel dieser Studie ist es, einen Werkzeuggriff mit maximaler Grip-Qualit t f r den Hammer im Falle eines Kraftgriffs zu entwerfen. Der Fokus dieser Studie ist haupts chlich darauf beschr nkt, die richtigen Querschnittsdurchmesser des Werkzeuggriffs zu identifizieren, basierend auf der Optimierung der Griffqualit tsfunktion mit Hilfe der Technik des Genetischen Algorithmus. Und eine Kreuzverifizierung der Ergebnisse wird auch durch subjektive Experimente einer Gruppe von Probanden durchgef hrt, um die ungef hre Dimension zu finden, die in der Komfortwahrnehmung der Probanden berragt. In dieser Studie soll ein neuer Weg zur Gestaltung eines Werkzeuggriffs vorgestellt werden.
L'utilisation d'outils main est encore largement appr ci e dans les industries diff rents niveaux. L'application des outils main varie d'une t che simple comme le martelage des t ches compliqu es, complexes et exigeantes en pr cision comme celle des scalpels chirurgicaux. Si un utilisateur travaille de mani re r p t e et continue avec un manche d'outil mal con u, il peut souffrir de troubles traumatiques cumulatifs (TTC), d'o l'importance de concevoir un manche d'outil qui soit "confortable" pour l'utilisateur. L'objectif de cette tude est de concevoir un manche d'outil avec une qualit de pr hension maximale pour le marteau en cas de prise de force. L'objectif de cette tude se limite principalement identifier les bons diam tres de section transversale du manche de l'outil, en se basant sur l'optimisation de la fonction de qualit de la poign e l'aide de la technique de l'algorithme g n tique. Et une v rification crois e des r sultats est galement effectu e par l'exp rimentation subjective d'un groupe de sujets et de trouver la dimension approximative qui se d marque dans la perception du confort du sujet. Dans cette tude, une nouvelle fa on de concevoir un manche d'outil doit tre introduite.
L'uso degli utensili manuali ancora ampiamente apprezzato nelle industrie a vari livelli. L'applicazione degli utensili manuali varia da un compito semplice come il martellamento a compiti complicati, complessi e che richiedono precisione come quelli dei bisturi chirurgici. Se un utente lavora ripetutamente e continuamente con un'impugnatura impropria, pu soffrire di un disturbo da trauma cumulativo (CTD), quindi diventa essenziale progettare l'impugnatura per il "comfort" dal punto di vista dell'utente. Lo scopo di questo studio quello di progettare una maniglia per utensili con la massima qualit di presa per il martello in caso di presa di potenza. L'obiettivo di questo studio principalmente limitato a identificare i diametri trasversali giusti della maniglia dell'utensile, basati sull'ottimizzazione della funzione di qualit Grip con l'aiuto della tecnica dell'algoritmo genetico. E una verifica incrociata dei risultati fatta anche attraverso la sperimentazione soggettiva di un gruppo di soggetti e trovare la dimensione approssimativa che si distingue nella percezione del comfort del soggetto. In questo studio, viene introdotto un nuovo modo di progettare una maniglia per utensili.
Użycie narzędzi ręcznych jest nadal szeroko doceniane w przemyśle na r żnych poziomach. Zastosowanie narzędzi ręcznych waha się od prostych zadań, takich jak uderzanie mlotkiem do skomplikowanych, zlożonych i wymagających precyzji zadań, takich jak skalpele chirurgiczne. Jeśli użytkownik pracuje wielokrotnie i w spos b ciągly z niewlaściwie zaprojektowaną rękojeścią narzędzia, może cierpiec z powodu kumulacyjnego zaburzenia urazowego (CTD), stąd niezwykle istotne staje się zaprojektowanie rękojeści narzędzia dla "komfortu" z perspektywy użytkownika. Celem niniejszej pracy jest zaprojektowanie uchwytu narzędzia z maksymalną jakością chwytu dla mlotka w przypadku chwytu silowego. Badania koncentrują się gl wnie na identyfikacji wlaściwych średnic przekroju poprzecznego uchwytu narzędzia, w oparciu o optymalizację funkcji jakości chwytu z pomocą techniki Algorytmu Genetycznego. Weryfikacja krzyżowa wynik w jest r wnież dokonywana poprzez subiektywne eksperymenty na grupie badanych i znalezienie przybliżonego wymiaru, kt ry wyr żnia się w postrzeganiu komfortu przez badanych. W tym badaniu, nowy spos b projektowania rękojeści narzędzia ma byc wprowadzony.
O uso de ferramentas manuais ainda muito apreciado nas ind strias a v rios n veis. A aplica o de ferramentas manuais varia desde uma tarefa simples como martelar at tarefas complicadas, complexas e exigentes em termos de precis o, tais como a de bisturis cir rgicos. Se um utilizador trabalha repetida e continuamente com um cabo de ferramentas mal concebido pode sofrer de dist rbio de trauma cumulativo (DTC), tornando-se assim altamente essencial conceber o cabo de ferramentas para "conforto" do ponto de vista do utilizador. O objetivo deste estudo projetar um cabo de ferramenta com a m xima qualidade de Grip para martelos em caso de pega de energia. O foco deste estudo limita-se principalmente a identificar os di metros transversais certos do cabo da ferramenta, com base na otimiza o da fun o de qualidade de Grip com a ajuda da t cnica de Algoritmo Gen tico. E uma verifica o cruzada dos resultados tamb m feita pela experimenta o subjetiva de um grupo de sujeitos e encontrar a dimens o aproximada que se destaca na percep o de conforto do sujeito. Neste estudo, uma nova forma de desenho de um punho de ferramenta deve ser introduzida.
