New Titles

Enhanced plant species identification via hierarchical modeling and multi-organ analysis

Javed, Hassan,

Abstract Accurate plant species classification is a critical componernt of biodiversity conservation, ecological research, and agricultural management. Traditional methods of species identification, relying heavily on morphological characteristics, are often timeconsuming, labor-intensive, and prone to errors, especially when dealing with morphologically analogous species or species with subtle differentiating traits. To address these challenges, this study introduces an artificial intelligence (AI)-driven approach that integrates Vision Transformer (ViT) models with metadata fusion, aiming to enhance both classification accuracy and robustness in complex species classification scenarios. The proposed model demonstrated remarkable performance, achieving a test accuracy of 97.27% and a Mean Reciprocal Rank (MRR) of 0.9842, which indicates a high degree of generalization across diverse plant species. This performance highlights the model's capacity to handle large-scale, high-dimensional plant data while maintaining high precision in species classification. Efficient utilization of GPU resources (RTX 3090 with 18GB memory) allowed for the smooth processing of large datasets, facilitating Tapid model training and evaluation. The integration of metadata, which includes environmental and taxonomic information, played a pivotal role in enhancing the model's ability to distinguish between morphologically similar species, a common challenge in plant species identification. A comparative analysis with previous Al-based plant classification models revealed that the proposed hybrid approach significantly outperformed traditional nmethods, particularly in cases where species exhibited similar morphological features. The ability to incorporate metadata alongside image-based features provides a robust framework for overcoming the limitations of conventional deep learning models, which typically rely solely on spatial feature extraction. This study's results have practical implications for several fields, including biodiversity conservation, ecological monitoring, and agriculture. By enabling accurate and effícient plant species identification, the proposed model can support real-time monitoring of plant populations, inform conservation efforts, and aid in agricultural decisionmaking. Future work will explore the integration of additional data modalities, such as hyperspectral imaging and genomic sequencing, to further improve classification accuracy and scalability. Through continued advancements in multi-modal data integration, this approach holds promise for further enhancing the reliability and applicability of A-driven plant species classification across diverse ecological settings.

Date Published:2024

Enhanced U-net segmentation using attention-guided ensemble technique

Ahmad, Hassan,

Abstract Pulmonary embolism (PE) is a severe clinical condition that may lead to life-threatening consequences if patients timcly and accurate diagnosis is not achieved. This research work introduces a novel framework for the PE segmentation from CTA images to include deep learning technologies for classification as well as segmentation. For slice classification, the framework uses an Attention-Guided Convolutional Neural Network (AG-CNN) the if which has a sensitivity of 94.8% and specificity of 92.3% using Inception-V3 as a backbone. An ensemble of Eficient Det, YOLOv8, and Faster R-CNN is trained for the detection of emboli: mAP = 89.6%; WBF improves localization. The segimentation tasks are perfornmed using AG-CNN with a U-Net model, for which the Dice Similarity Coefficient (DSC) is 93.2% and Intersection over Union (IoU) score is 73.7%, allowing better demarcation of the emboli. The framework works computationally, and it takes less than 0.3 second to complete a single image on a working on a system with meager computing power. Incorporating powerful classification, detection, and segmentation methods, this work helps alleviate difficulties comparable to lesion variation, mathematical differences in features, and peripheral emboli visualization.

Date Published:2024

A data-driven approach for automated quality concern extraction from App reviews

Hussain, Maryam,

Abstract The overwhelming growth in mobile applications has resulted in a huge influx in the number of user-generated reviews in the application stores such as Google Play Store. The reviews provide a good feedback on the software quality attributes such as usability, performance, security, and reliability. Nevertheless, they are unstructured, informal and usually ambiguous, which presents significant difficulties in the manual analysis. The availability of traditional machine learning (ML) and deep learning (DL) methods has helped in the automation of this step, but they usually use handcrafted features and do not understand the situation in a deep perspective, which limits their usefulness in multi-label classification tasks. This study offers a powerful and scalable model that uses Transformer-based models to automatically extract quality concerns in the reviews of mobile apps. The method is based on the self-attention mechanisms and contextual embeddings, which helps to increase semantic understanding and minimize the reliance on the handcrafted feature engineering. The extracted concerns are grouped based on the ISO 25010 standard that facilitates systematic and understandable quality evaluation. Other issues the study addresses include class imbalance, implicit concern recognition, and cross-domain generalization. To evaluate the performance, a dataset of 20,000 real-world app reviews is employed, and performance is measured using the concepts of precision, recall, F1-score and comparative evaluation with ML/DL baselines. It is expected to result in a multi-label classification and recommendation service which further enhances the automation and precision of software quality analysis, and provides developers and quality assurance teams with actionable advice Keywords: Mobile App Reviews, Software Quality Concern Extraction, Transformer-based Models, Multi-label Classification, ISO 25010 Quality Attributes, Automated Quality Assessment.

Date Published:2025

Integrating process intelligence into Software Development Life Cycle (SDLC)

Farooqui, Muhammad Rohan Zahid,

Abstract Despite advancemnents in the Software Development Life Cycle (SDLC), inefficiencies and project failures continue to pose significant challenges for software organizations. Process intelligence, encompassing techniques such as process mining, task mining, and business intelligence, offers the potential to enhance real-time visibility and decision-making throughout the Software Development Life Cycle (SDLC). HOwever, existing techniques do not provide a structured set of guidelines for analyzing the development process and exhibit limited integration into formal Software Development Life Cycle (SDLC) models. Moreover, these techniques often fall short in effectively identifying inefficiencies across various stages of the Software Development Life Cycle (SDLC). This study proposes a theoretical framework for systematically embedding process intelligence into each stage of the Software Development Life Cycle (SDLC). The proposed framnework offers structured guidance to stakeholder's for identifying inefficiencies, optimizing workflows, and promoting continuous improvement by leveraging real-time process data.

Date Published:2025

Fixed points of generalized contraction and non expansive mappings with application

Dilawer, Hina

Introduction 1.1 Historical Framework of Fixed Point Theory 1.1.1 Fixed Point Theory 1.1.2 Banach Contraction Principle 1.1.3 Generalized Mappings 1.1.4 Multivalued Contraction Mappings 1.1.5 Nonexpansive Mappings 1.1.6 Enriched Mappings 1.1.7 Fractals 1.2 Problem Statement 1.3 Thesis Plan 2 Literature Review 20 Introduction 2.1.1 Generalized Contractions 2.1.2 Nonexpansive Mappings 2.1.3 Iterative Methods 2.1.4 Graphical Metric Space 2.1.5 Common Fixed Points 2.1.6 G-metric Space and G-norm 2.1.7 Fractals 3. Preliminaries 3.1 Basic Concepts 3.1.1 Notations 民間祭2 Netric and Banach space 3.1.4 0-contractions 3.1.5 Binary relation 3.1.10 F-contractions 3.1.11 Convergence and Stability 3.1.17 Generalized Mappings and Fixed Point 3.1.27 Iterative Algorithms 3.1.28 Graph 3.1.31 G-metric and G-norm Space 4 Multivalued Weak Suzuki Type (0.R) Contraction cations 4.1 Introduction 4.2 Multivalued Weak Suzuki Type (6. R) contraction 4.3 Application in Data Dependence 4.4 Existence of Solution of Nonlinear Matrix Equation 4.5 Conclusion 5 Convergence and w²-Stability Analysis of a Hyb tive Scheme with Application to Functional De Equations 5.1 Introduction 5.2 Convergence Theorems 5.3 Weak 2-Stability 5.4 Numerical Experiments and Graphical Analys 5.5 Application to Volterra-Stieltjes-Type Delay 5.6 Concluding Remarks 6 A Novel AA Method for Exploring the Interplay Between Frac- tals, Polynomiographs, and Fractional Calculus 6.1 Introduction 6.2 Results on Convergence 6.3 Analytical Rate of Convergence 16.4 Discussion 6.4.1 Graphical Analysis of Convergence and Time Efficiency 6.5 Polynomiographs 6.6 Application to the Solution of Delay Differential Equation 16.7 Conclusions Exploring the Existence of Solution of Nonlinear Fredholm Inte gral Equations: Novel Approaches to Estimating Common Fixe Points 7.1 A Modified AA-Iterative Scheme for Garcia-Falset Mappings 7.2 Graphical Garcia Falset mappings and Convergence Analysis 7.3 Example and Numerical Experiments 7.4 Application to the Solution to Nonlinear Fredholm Integral Equa tion Equipped with Graph 7.5 Discussion 7.6 Conclusion 18 G-Norm Enriched Iterated Function Systems and Fractal 8.1 Introduction 8.1.1 G-norm Enriched F-Contraction and G-Enriched F-Cont 8.2 Main results 8.3 Iterated Function System Conculsion . In this thesis, the idea of multivalued weak Suzuki Type (0,R) contractions is presented whose single valued version is also novel in literature. A fixed point re-sult in the frame of metric space endowed with binary relation for such a mapping is established and some examples are provided. Data dependence of fixed points and existence of solution of matrix equations are also discussed as an application of results. A hybrid-type iterative algorithm for a class of generalized non-expansive map-pings satisfying the Garcia-Falset property in uniformly convex Banach spaces is analyzed. Some existing results for such mappings have been obtained using the given algorithm. The w²-stability of the iterative process is also studied. Using some examples, numerical experiments are conducted. A weak solution of the Volterra Stieltjes type delay functional differential equation is presented to demonstrate the significance of the proposed results. Further, a new numerical method, the AA-iterative method is introduced, for approximating fixed points of symmetric generalized nonexpansive mappings in uniformly convex Banach spaces. We demonstrate its significant rate of conver-gence and applicability in generating fractal patterns and polynomiographs. We establish the existence and uniqueness of solutions for delay fractional differential equations, providing a comprehensive analysis of foundational aspects. An an innovative numerical approach for estimating fixed points of symmetric generalized nonexpansive mappings within uniformly convex Banach spaces is introduced. This approach demonstrates a notably quicker convergence rate rel-ative to existing iterative methods. Its effectiveness is confirmed through compre-hensive numerical tests, comprising CPU time comparisons and visual represen-tations created in MATLAB, including polynomiographs. Additionally, using the proposed method, we show that solutions to a type of delay fractional differential equations exist and are unique. This investigation is performed within the scope of Garcia-Falset type mappings, a wider category that includes nonexpansive and Suzuki mappings, thus broadening the relevance of our method. This study also explores common fixed points for mappings that satisfy the non-symmetric Garcia-Falset property in a Banach space with uniform convexity and a digraph G. By leveraging coordinate convexity, the convergence results of the modified AA-iterative algorithm have been analyzed. The aim is to identify com-mon fixed points through a series of convergence analyses and offer an illustrative example to validate findings for such mappings. Examples are presneted and the existence of a common solution to a system of nonlinear Fredholm integral equa-tions has been established. Finally, we presents a new class of operators, called G-norm enriched F-contractions, defined on G-Banach spaces. Using Krasnoselskii's iteration method, we estab-lish convergence results for the fixed points of these operators. These results are then applied to creating fractals related to the Hutchinson-Barnsley operator. To achieve this, we introduce a novel iterated function system (IFS), the G-norm IFS, which utilizes the properties of G-norm enriched F-contractions. Several examples demonstrate the convergence of the G-norm IFS to its attractor. Ad-ditionally, we show the existence and approximation of fractals generated by this construction, employing G-norm fractal interpolation functions.

Date Published:2026

The impact of social network properties on knowledge hiding bevaior of employees.

Aroosa,Safdar,

The thesis is submitted to the FAST School of Management in partial fullfilment of the requirements for the degree of philosophy in Management Sciences at the National Unversity of Computer and Emerging Sciences Islamabad Pakistan. Publications originated from this dissertation List of Figures List of Tables List of Abbreviations Chapter 1 Introduction Dissertation gap identification Research objectives and questions Study 1 Examining the mediating role of knowledge hiding in the relationship between degree centrality and social capital A moderated mediation model Brief overview Antecedents and consequences of knowledge hiding Study 2 Why and when employees degree centrality influences knowledge hiding A moderated mediation model Brief overview Antecedents and mechanisms underlying knowledge hiding Scope Industry context of the dissertation Research contribution Definition of main constructs Degree centrality Knowledge hiding Social capital Fear of losing power Social astuteness Competitive psychological climate United nations sustainable development goals SDG 8 Decent work and economic growth SDG 9 Industry innovation and infrastructure Structure of the dissertation Chapter summary Chapter 2 Literature Review Research variables Network centrality and degree centrality Fear of losing power Knowledge hiding Social capital Social astuteness Competitive psychological climate Study 1 Examining the mediating role of knowledge hiding in the relationship between degree centrality and social capital A moderated mediation model Theory and hypotheses Degree centrality and social capital Conservation of resource theory Social exchange theory Knowledge hiding as a mediator Social astuteness as a moderator Study 2 Exploring knowledge hiding in social networks Investigating the role of power dynamics fear of losing power and competitive psychological climate Theory and hypotheses Degree centrality and fear of losing power Fear of losing power and knowledge hiding Fear of losing power as a mediator Competitive psychological climate as a moderator Consolidated concept of the dissertation Chapter summary Chapter 3 Methodology Introduction Research philosophy Research strategy and approach Study 1 Examining the mediating role of knowledge hiding in the relationship between degree centrality and social capital A moderated mediation model Sample and procedure Measurement scale Independent variable Degree centrality Dependent variable Social capital Mediating variable Knowledge hiding Moderating variable Social astuteness Control variables Study 2 Why and when employees degree centrality influences knowledge hiding A moderated mediation model Sample and procedure Statistical analysis Common method variance Measurement scale Degree centrality Fear of losing power Knowledge hiding Competitive psychological climate Control variables Chapter 4 Results and discussion Study 1 results Descriptive statistics and correlation matrix Common method variance Measurement model Hypotheses testing Study 1 discussion Study 2 results Descriptive statistics and correlation analysis Measurement model Hypothesis testing Study 2 discussion Chapter summary Chapter 5 Conclusion Introduction Study 1 Examining the mediating role of knowledge hiding in the relationship between degree centrality and social capital A moderated mediation model Implications Theoretical implications Managerial implications Limitations Future research directions Study 2 Why and when employees degree centrality influences knowledge hiding A moderated mediation model Implications Theoretical implications Managerial implications Limitations Future research directions Dissertation consolidated conclusion Chapter summary References Appendices . Knowledge hiding in organizations undermines collaboration, trust, and social capital, yet the structural and psychological mechanisms that drive this behavior remain underexplored. In particular, the role of employees' social network positions in shaping knowledge hiding has received limited attention, despite its critical implications for knowledge flows and organizational performance. Drawing on Conservation of resources theory, social exchange theory, and psychological ownership theory, this dissertation investigates how employees' centrality in organizational networks influences their defensive knowledge behaviors, highlighting the interplay between structural, psychological, and contextual factors. The first study examines how employees' degree centrality impacts social capital through knowledge hiding, with social astuteness moderating the process at multiple stages. Using survey data from 214 service-sector employees in Pakistan, the study finds that knowledge hiding mediates the relationship between degree centrality and social capital, while social astuteness shapes the strength and direction of this effect. Individuals with higher social astuteness can navigate network dynamics strategically, mitigating the negative consequences of knowledge hiding and sustaining social capital. The second study explores why central employees engage in knowledge hiding by introducing fear of losing power as a mediator and competitive psychological climate as a moderator. Data collected from 265 employees across service industries reveal that employees' centrality increases fear of losing power, which in turn drives knowledge hiding behaviors, and that a competitive psychological climate amplifies this indirect effect. Psychological ownership further explains why employees perceive knowledge as a personal resource, intensitying defensive withholding behaviors in competitive environments. Together, these studies advance knowledge hiding research by integrating social network analysis with Conservation of resources theory, social exchange theory, and psychological ownership theory, providing a nuanced understanding of how structural positions, psychological perceptions, and workplace climates jointly shape knowledge-sharing behaviors. The dissertation offers theoretical insights by linking network centrality to resource preservation, relational obligations, and power dynamics; methodological contributions through robust, multi-study quantitative designs; and practical guidance for managers to foster reciprocal knowledge exchange, mitigate defensive behaviors, and balance the benefits of central network positions with the risks of power struggles. Ultimately, this research informs organizational strategies to enhance collaboration, trust, and innovation, particularly in developing economies and service-sector contexts. Keywords: degree centrality, social astuteness, social capital, knowledge hiding, fear of losing power, competitive psychological climate, social network analysis.

Date Published:2026

Enabling Analytics Transformation for Data-Informed Decisions : Augmented Analytics:

Weber, Willi,

Date Published:2000

Corporate law and governance : principles and practice

Cohen, Charles C.,

Foundations of Corporate Law, Governance, and Finance -- The Embedded "Agency Problem" Within the Board of Directors -- Roles of the Individual Officer and Director -- Committees on the Board of Directors -- The Business Judgment Rule -- Selection and Compensation of Executives -- Monitoring and Compliance Duties -- Expansion of Oversight and Monitoring Duties -- Exculpation and Indemnification from Liabilities for Breach of Fiduciary Duties -- Shareholder Derivative Claims -- Related Party Transactions -- Competing for Business Opportunities -- Introduction to Business Combinations -- Insider-Led Buyouts and "Going Private" -- Third-Party Takeover Offers and Bids -- Shareholder Primacy and Twenty-First-Century Federal Protections -- Election of Directors and Federal Regulation of the Proxy Process -- Market Initiatives -- Corporate Charity and Social Responsibility -- Environmental, Social, and Governance -- Corporate Diversity, Equity, and Inclusion. "Law school casebook for upper-level students combining relevant coverage of corporate law with a focus on corporate governance"--

Date Published:2025

Business Law Dynamics (CAF-4 )

Date Published:2025

Personalized : Customer Strategy in the Age of AI

Abraham, Mark (Partner at BCG),

Includes index. The personalization advantage -- Part I: the promises of personalization -- Empower me -- Industry spotlight: travel -- Know me -- Industry spotlight: financial services -- Reach me -- Industry spotlight: retail -- Show me -- Industry spotlight: fashion and beauty -- Delight me -- Industry spotlight: health care -- Building personalization through smart integration -- Industry spotlight: B2B distribution and technology -- Part II: leading the transformation -- Expanding roles in the c-suite -- Measuring impact -- Navigating risk and privacy -- Competing on personalization -- Personalization of the future. "Research shows that the vast majority of consumers want personalized experiences, and a select few companies are rising to the challenge. These personalization leaders build trusted relationships with millions of customers across channels and engage with them at every step throughout their journey. They are rethinking their operations and unleashing the creativity of their teams-combined with the power of AI and technology-to fine-tune each successive interaction, delighting customers in the process. Most companies, though, are not doing personalization well, leading to wasted money, squandered effort, and missed expectations. To be done effectively, personalization must be a critical element of your organization's strategy. Personalized is a playbook to deliver true personalization at scale. In this book, Boston Consulting Group's Mark Abraham and Harvard Business School's David C. Edelman describe the Five Promises of Personalization that companies must live up to: Empower Me: Understand each customer's unique needs and decide how to best help them; Know Me: Win customers' trust and permission to securely use their data to improve their experience; Reach Me: Reach out to the right customer, in the right channel, at just the right moment; Show Me: Tailor unique content to be relevant to each customer, enabled by generative AI; Delight Me: Design new ways of working and processes to speed up the velocity of continuous improvement and make a customer's experience feel magical. With detailed examples across industries-including retail, health care, banking, B2B, technology, fashion, and travel-this book will help executives learn how to put personalization at the center of their strategy, accelerate growth, and capture their share of the $2 trillion personalization prize"--

Date Published:2024

The Ethics of AI : Power, Critique, Responsibility

MuÌhlhoff, Rainer.

Front Cover -- The Ethics of AI: Power, Critique, Responsibility -- Copyright Page -- Table of Contents -- List of Figures and Tables -- About the Author -- Acknowledgements -- Introduction: What Does It Mean to âDoâ a Power-.Aware Ethics of AI? A Note to Readers -- Structure of the book -- Subjectivity and power in contemporary AI -- Contemporary AI as prediction power -- AI and social structures -- Collective responsibility -- Intervening in the ethics of AI: a systematic delineation of the power-.aware approach -- Part I The Power of AI -- 1 What AI Are We Talking About? -- Humanâcomputer interaction and âgenius AIâ -- Ethics of AI beyond anthropomorphism -- Contemporary AI systems as hybrid computing networks -- 2 Human-Aided AI -- The first thesis of Human-Aided AI -- Example: Facebookâs DeepFace project -- The second thesis of Human-Aided AI -- Click-work -- Commercial content moderation and the social costs of click-work -- The third thesis of Human-Aided AI -- AI extractivism and digital colonialism -- 3 Digital Counter-Enlightenment and the Power of Design -- AI in the history of networked media -- Interface nudges and digital choice architectures This book critically examines the ethical and societal challenges posed by artificial intelligence (AI) technologies, focusing on power dynamics, subjectivity, and the role of predictive systems. Written by philosopher and mathematician Rainer MÃ¼hlhoff, it integrates philosophy, media studies, and computer science to develop a contemporary critique of AI's impact on society. The author explores concepts such as 'predictive privacy,' 'control power,' and 'collective ethics,' arguing for a power-aware approach to AI ethics that transcends traditional applied ethics frameworks. Targeted at scholars and ethical agents, the book seeks to inspire public and political engagement with systemic issues in AI development and usage. It advocates for a structural and philosophical critique to address the capitalist-driven complexities of AI systems.

Date Published:2025

Tableau Certified Data Analyst study guide : learn the core concepts and techniques necessary to ace the exam

Gardner, Christopher, 1957-,

Gaining a Tableau Certified Data Analyst title is key to advertising your skill set in a data-hungry world. It advertises your ability to connect to, analyze, and describe data in an industry-leading data-visualization tool. This study guide provides example questions, terminology, walkthroughs, and best practices to help you learn key topics covered by this certification exam. Christopher Gardner, business intelligence analyst and lead Tableau developer for the University of Michigan, provides guidelines for first-time test-takers and a comprehensive review for Tableau veterans. You'll start by learning how to use Tableau's data Prep Builder and the Tableau Desktop software to connect to, prepare, manipulate, and combine datasets. Then you'll dive into the build interface to develop simple yet compelling data visualizations before moving into more complex topics such as table calculations, level-of-detail expressions, parameters, and predictive analytics tools.

Date Published:2025

Financial markets and institutions : Evergreen Release

Saunders, Anthony

Previous edition: 2012. Text on inside of front and back covers. "Pearson Global Edition." -- Back cover. Includes access to companion website. For all undergraduate and graduate students of Financial Markets. This title is also suitable for all readers interested in financial markets and institutions. A practical and current look into today’s financial markets and institutions. In Financial Markets and Institutions , bestselling authors Frederic S. Mishkin and Stanley G. Eakins provide a practical introduction to prepare students for today’s changing landscape of financial markets and institutions. A unifying framework uses core principles to organize students’ thinking then examines the models as real-world scenarios from a practitioner’s perspective. By analyzing these applications, students develop the critical-thinking and problem-solving skills necessary to respond to challenging situations in their future careers. Although this text has undergone a major revision, the Eighth Edition retains Mishkin/Eakins’ hallmark pedagogy that make it the best-selling textbook on financial markets and institutions. This program will provide a better teaching and learning experience–for you and your students. Here’s how: Organize Learning with a Unifying Analytic Framework: Core principles organize students’ thinking and then examine the models as real-world scenarios from a practitioner’s perspective. Help Students Transition from Classroom to Career with Real-Life Business Scenarios: Cases increase students’ interest by applying theory to real-world data and examples. Emphasis Critical Thinking with Key Features : Examples and exercises allow students to put into practice the concepts that they are learning. Keep Your Course Current and Relevant: New material on financial markets and institutions and monetary policy appear throughout the text.

Date Published:2016

Web Applications with ASP.NET Core Blazor : Create Powerful, Responsive, and Engaging Web Applications.

Ding, Brian,

Cover -- Half Title -- Title -- Copyright -- Dedication -- Contents -- Preface -- Acknowledgments -- About the Author -- About the Reviewer -- Chapter 1: WebAssembly Introduction -- Introduction -- Structure -- Objectives -- What Is WebAssembly -- History of WebAssembly -- Hello World! with WebAssembly -- Call WebAssembly from JavaScript -- WebAssembly in the Future -- Popular WebAssembly Languages -- .NET Core -- ASP.NET Core -- When to Choose ASP.NET Core Blazor -- Conclusion -- Chapter 2: Choose Your Hosting Model -- Introduction -- Structure -- Objectives -- WebSocket -- SignalR -- Blazor Server -- Blazor WebAssembly -- Blazor Hybrid -- Conclusion -- Chapter 3: Implementing Razor and Other Components -- Introduction -- Structure -- Objectives -- Razor Components -- Directive -- Directive Attribute -- One-Way Binding -- Binding Event -- Binding Format -- Unparsed Value -- Two-Way Binding -- Cascading -- Event Handling -- Lifecycle -- Layout -- Libraries -- Fast-Blazor -- MatBlazor -- Ant Design Blazor -- BootstrapBlazor -- Conclusion -- Chapter 4: Advanced Techniques for Blazor Component Enhancement -- Introduction -- Structure -- Component Reference -- Components Preserving -- Template Components -- CSS Isolation -- Conclusion -- Chapter 5: File Uploading in Blazor -- Introduction -- Structure -- Objectives -- Build Comments for EShop -- File Transfer -- File Upload -- Tips -- Conclusion -- Chapter 6: Serving and Securing Files in Blazor -- Introduction -- Structure -- Objectives -- Middleware -- Serve Static Files -- Serve Dynamic Files -- Security Advice -- Conclusion -- Chapter 7: Collecting User Input with Forms -- Introduction -- Structure -- Objectives -- Forms -- EditForm -- InputBase -- Validation -- Custom Validation -- Form Submission -- EditContext and Form State -- Conclusion -- Chapter 8: Navigating Over Application. Introduction -- Structure -- Objectives -- Router -- RouteAttribute -- NavLink -- Route Parameters -- Navigation Events and Asynchronous Navigation -- ASP.NET Core Integration -- Conclusion -- Chapter 9: .NET and JavaScript Interop -- Introduction -- Structure -- Objectives -- Serialization -- Loading JavaScript -- Initializer -- Calling JavaScript from .NET -- JavaScript Isolation -- Calling .NET from JavaScript -- Cache -- Element Reference -- Type Safety -- Conclusion -- Chapter 10: Connecting to the World with HTTP -- Introduction -- Structure -- Objectives -- Front-End and Back-End Separation -- HTTP Protocol -- Cross-Origin Resource Sharing -- HTTPClient -- HTTPClientFactory -- HTTPClient Again -- gRPC -- Conclusion -- Chapter 11: Data Persistence with EF Core -- Introduction -- Structure -- Objectives -- Stateless and Stateful -- EntityFramework Core -- Context Object -- Data Entities -- Database Migration -- Data Update -- Data Query -- Conclusion -- Chapter 12: Protecting Your Application with Identity -- Introduction -- Structure -- Objectives -- Authentication -- AuthenticationStateProvider -- Authorization -- Role-Based Authorization -- Policy-Based Authorization -- ASP.NET Core Identity -- Conclusion -- Chapter 13: Deploying with Docker and Kubernetes -- Introduction -- Structure -- Objectives -- What Is Docker? -- Building a Docker Image -- Image Layer -- What Is K8S? -- K8S Components -- Deploy to AKS-K8S on Azure -- Conclusion -- Index. This book covers many different aspects of developing Blazor applications, a modern way to build rich UI web apps. It also introduces methods to leverage .NET and its eco-systems to build a modern enterprise application. It features WebAssembly and how it can be written in any programming language. The book also compares different Blazor hosting models and the strategy to select a model that suits specific business requirements. It is designed for web developers, software engineers, and tech enthusiasts looking to build robust, interactive web applications using ASP.NET Core Blazor. Using a demonstrative approach for Blazor learners, every chapter includes numerous code examples and a Blazor source code analysis. It covers basic Blazor directives and components and how these concepts can be combined together to build a more complex customized component. Master modern deployment techniques with Docker and Kubernetes. This book also explains some advanced techniques to control component rendering and improve performance. Companion files with code samples and color figures are available for downloading.FEATURESâ¢Features code examples and detailed analysis to help you grasp Blazor concepts effectivelyâ¢Learn advanced component enhancement, performance optimization, and secure file handlingâ¢Master modern deployment techniques with Docker and Kubernetes, ensuring your applications are production-readyâ¢Download companion files with code samples and color figures.

Date Published:2024

The Infinite Retina: Navigate Spatial Computing, Augmented and Mixed Reality, and the next tech revolution

Cronin, Irena,

Includes index. What is Spatial Computing, and why are companies like Tesla, Apple, and Meta investing billions into it? In The Infinite Retina, Irena Cronin and Robert Scoble explore how spatial computingâwhere humans and machines interact in a digitalâphysical spaceâhas progressed beyond theory into real-world applications. This second edition has many substantial updates, including two new chapters on the relevance of Generative AI in Spatial Computing and a new chapter on the impact of Apple Vision Pro. Each existing chapter has been updated to have the most current information and commentary. The book offers a fresh look at seven major industries, including healthcare and retail, featuring updated case studies, expert commentary, and real-world examples. Additionally, it addresses crucial risks and challenges, such as data privacy, automation's impact on employment, and ethical concerns. This edition moves beyond speculation to critically analyze what Spatial Computing means for businesses and individuals today.

Date Published:2025

PCI DSS Version 4.0.1: A Guide to the Payment Card Industry Data Security Standard

Hancock, Stephen.

This book explains the fundamental concepts of PCI DSS v4.0.1.

Date Published:2025

Machine Learning Essentials You Always Wanted to Know: A Hands-On Beginner’s Guide to Mastering AI, Supervised, Unsupervised, and Deep Learning Algorithms

Vibrant Publishers (Broomfield, Colorado),

Date Published:2025

Getting Started with Docke and AI

Poulton, Nigel

Book.

Date Published:2023

Deep Learning with Python

Chollet, Francois

Description based upon print version of record. The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX!Deep Learning with Python, Third Edition puts the power of deep learning in your hands.This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX.

Date Published:2026

Cybersecurity Awareness

Pils, Martin

Date Published: