AI In Cybersecurity
AI in Cybersecurity: The Ultimate Guide for Modern Threat Defense in the Digital Age In an era where data is currency and cyberattacks are more sophisticated than ever, businesses and individuals alike must rethink their approach to digital security. AI in Cybersecurity is the definitive resource that explores how artificial intelligence is transforming cyber defense systems, offering proactive, intelligent, and scalable protection in an evolving threat landscape.This comprehensive guide dives deep into the intersection of artificial intelligence and cybersecurity. Whether you're a small business owner, IT professional, executive, or tech enthusiast, this book delivers actionable insights, up-to-date frameworks, and practical use cases that show how AI is being deployed to detect threats, prevent breaches, and predict vulnerabilities before they become catastrophic.���� What You'll Learn Inside This Book: How machine learning and deep learning algorithms are used for real-time threat detection.The role of AI in identifying phishing attacks, malware, ransomware, and insider threats.Case studies from organizations using AI to secure data, networks, and cloud infrastructure.Key differences between rule-based systems and AI-driven defense.The impact of natural language processing (NLP) on analyzing threat intelligence and dark web chatter.Practical tools and platforms that leverage AI for cybersecurity automation and risk scoring.Ethical implications of AI-powered surveillance and privacy enforcement.How AI can help SMBs, enterprises, and government agencies scale their cybersecurity efforts.Unlike traditional cybersecurity books that focus only on manual defenses or complex technical concepts, AI in Cybersecurity is crafted to be accessible, insightful, and practical. Readers gain a strategic overview of how AI is enhancing digital resilience while also receiving real-world tactics that can be implemented immediately.���� Who This Book Is For: Small and Medium Businesses (SMBs) looking to protect their digital assets without large IT budgets.Cybersecurity professionals who want to upskill and stay ahead of AI-driven threat vectors.CISOs, CTOs, and IT managers responsible for digital risk management and compliance.Tech students and educators exploring the future of secure AI-driven infrastructure.Entrepreneurs and startups aiming to embed cybersecurity into their AI products from day one.���� Why It Matters Now More Than Ever: Cybercrime is projected to cost the global economy over $10 trillion annually by 2025. As threats evolve faster than human teams can respond, AI offers a revolutionary leap forward-delivering speed.
Ai-Driven Marketing
AI-Driven Marketing: The Future of Smarter, Faster, More Profitable Campaigns Is HereDiscover how artificial intelligence is revolutionizing marketing-and how you can stay ahead of the curve.AI-Driven Marketing is the ultimate guide for marketers, entrepreneurs, freelancers, and business owners who want to harness the power of artificial intelligence to drive sales, boost productivity, and create personalized customer experiences at scale.This comprehensive book covers the most important areas of modern marketing-content creation, advertising, data analysis, SEO, social media, email automation, and customer segmentation-through the lens of AI and machine learning.Whether you're a solo creator or part of a marketing team, this book gives you practical, step-by-step strategies to integrate AI tools into your workflow with ease. Learn how to work smarter, not harder, and get better results with less effort.You'll also find insights on integrating AI with CRM platforms, streamlining workflows between marketing and sales, and using AI to build predictive customer journeys that anticipate buyer behavior. This guide goes beyond theory-it delivers the tools and know-how you need to build marketing systems that scale.What You'll Learn: ✅ AI-Powered Content Creation Discover how to use tools like ChatGPT, Jasper, and Copy.ai to generate high-converting ad copy, blog posts, and product descriptions in minutes.✅ Customer Segmentation & Personalization Use machine learning algorithms to tailor campaigns to your audience and dramatically increase engagement and ROI.✅ Automated Email & Social Media Marketing Master platforms that schedule and optimize outreach using AI, helping you nurture leads automatically and boost conversions.✅ Predictive Analytics & Data-Driven Decisions Learn how to analyze customer behavior using AI to forecast trends and make smarter marketing decisions.✅ AI for Ad Targeting & Budget Optimization Stop wasting ad spend. Use AI tools to pinpoint your ideal audience and test campaigns at scale for maximum ROI.✅ SEO Automation & Keyword Research Tap into AI platforms that streamline SEO research, analyze competitors, and optimize content for search rankings-fast.✅ Visual Content with AI Design Tools Create eye-catching graphics, social posts, and branding elements with no design experience-using AI-powered tools like Canva AI and Midjourney.✅ Ethical AI Use & Human Oversight Learn the importance of combining AI power with human creativity and ethical marketing practices.✅ Real-World Case Studies Dive into detailed case studies showing how real businesses are increasing revenue, cutting costs, and growing their audiences through AI.This book is written for non-technical readers-no coding, no jargon-just powerful, clear guidance. You'll walk away with a toolbox of AI resources, expert tips, and real-world examples you can apply immediately to grow your business and enhance your career.Whether you're just starting or looking to upgrade your marketing game, AI-Driven Marketing provides the blueprint for scaling your brand in the age of automation-and staying ahead of your competition.
Climbing the Tower of Babel
Machine translation of language isn't rocket science. It's even more difficult. Despite revolutionary leaps in hardware, software, and linguistics throughout the 20th century, technology has delivered only rudimentary solutions for a handful of the world's 6800 languages. By 2035, however, advances in computers and artificial intelligence, the convergence of information-based devices, and the maturity of linguistics and programming tools will dissolve barriers to language and bring game-changing transparency to this greatest human challenge. Perfect machine translation will permit instantaneous availability of all languages, fusion with video and imagery data-streams, and unprecedented multi-domain awareness. In short, machine translation will guarantee communication and understanding. Accordingly, the Air Force and the Department of Defense must plan now to integrate this spectacular capability to further a gamut of national security interests.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Robot Localizationusing Visualimage Mapping
One critical step in providing the Air Force the capability to explore unknown environments is for an autonomous agent to determine its location. The calculation of the robot's pose is an optimization problem making use of the robot's internal navigation sensors and data fusion of range sensor readings in calculating the most likely pose. This data fusion process requires the simultaneous generation of a map which the autonomous vehicle can then use for obstacle avoidance, communication with other agents in the same environment, and target location. Our solution entails mounting a Class 1 laser to an ERS-7 AIBO. The laser projects a horizontal line on obstacles in the AIBO camera's field of view. Range readings are determined by capturing and processing multiple image frames, resolving the laser line to the horizon, and extracting distance information to each obstacle. This range data is then used in conjunction with mapping and localization software to accurately navigate the AIBO.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Climbing the Tower of Babel
Machine translation of language isn't rocket science. It's even more difficult. Despite revolutionary leaps in hardware, software, and linguistics throughout the 20th century, technology has delivered only rudimentary solutions for a handful of the world's 6800 languages. By 2035, however, advances in computers and artificial intelligence, the convergence of information-based devices, and the maturity of linguistics and programming tools will dissolve barriers to language and bring game-changing transparency to this greatest human challenge. Perfect machine translation will permit instantaneous availability of all languages, fusion with video and imagery data-streams, and unprecedented multi-domain awareness. In short, machine translation will guarantee communication and understanding. Accordingly, the Air Force and the Department of Defense must plan now to integrate this spectacular capability to further a gamut of national security interests.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Applying Image Matching to Video Analysis
Dealing with the volume of multimedia collected on a daily basis for intelligence gathering and digital forensics investigations requires significant manual analysis. A component of this problem is that a video may be reanalyzed that has already been analyzed. Identifying duplicate video sequences is difficult due to differences in videos of varying quality and size. This research uses a kd-tree structure to increase image matching speed. Keypoints are generated and added to a kd-tree of a large dimensionality (128 dimensions). All of the keypoints for the set of images are used to construct a global kd-tree, which allows nearest neighbor searches and speeds up image matching. The kd-tree performed matching of a 125 image set 1.6 times faster than Scale Invariant Feature Transform (SIFT). Images were matched in the same time as Speeded Up Robust Features (SURF). For a 298 image set, the kd-tree with RANSAC performed 5.5 times faster compared to SIFT and 2.42 times faster than SURF. Without RANSAC the kd-tree performed 6.4 times faster than SIFT and 2.8 times faster than SURF. The order images are compared to the same images of different qualities, did not produce significantly more matches when a higher quality image is compared to a lower quality one or vice versa. Size comparisons varied much more than the quality comparisons, suggesting size has a greater influence on matching than quality.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Artificial Intelligence
Artificial intelligence (AI) is transforming multiple aspects of human life, raising fundamental questions: Is AI truly intelligent? Can it surpass human capabilities? What are its risks and opportunities? In this book, I aim to clarify what AI really is, debunking myths while offering a rigorous, balanced perspective on its impact. Rather than chasing the latest AI trends, I will focus on the core principles that define it, tracing its evolution from early pioneers like Alan Turing to today's advanced systems. AI remains in the realm of narrow intelligence, excelling at specific tasks but far from replicating human cognition. Yet, its ability to process vast data, predict behaviors, and generate creative content is reshaping industries, from healthcare to finance. At the heart of AI's progress is machine learning, particularly neural networks, which rely more on data-driven training than traditional scientific theory. However, this innovation comes with challenges: environmental costs, job market disruptions, ethical dilemmas, and the black box problem--AI's decision-making opacity, which raises concerns about trust and accountability. AI also plays a growing role in global power dynamics, influencing governance, security, and even democracy. Nations leading AI development gain strategic advantages, but without careful regulation, AI could fuel inequality, surveillance, and manipulation. Despite the fears AI evokes, it is neither an existential threat nor a magical solution. My goal is not to celebrate or demonize it but to provide a critical framework for understanding this technological revolution. By fostering awareness, we can shape AI's integration into society in a way that aligns with human values and scientific progress.
Knowledge Base Support for Design and Synthesis of Multi-Agent Systems
Agent Tool is an AFIT-produced, AFOSR-sponsored multi-agent system (MAS) development tool intended for production of MASs that meet military requirements. This research focuses on enabling MAS design and synthesis tools like agent Tool to store, retrieve, and filter persistent, reusable, and reliable agent domain knowledge. This "enabling" is vital if such tools are expected to produce consistent, maintainable, and verifiable agent applications on short timetables. Enabling requires: 1) modeling the agent knowledge domain, 2) designing and employing a persistent knowledge base, and 3) bridging that domain model to the knowledgebase with an extensible domain interchange grammar. The achieved interchange grammar, called Multi-Agent Markup Language (MAML), is presented and shown to be capable of representing MAS design knowledge in a concise and easily parsed form that is readily stored and retrieved in the knowledge base. The selected knowledge base, called the Agent Random-Access Meta-Structure (ARAMS), is shown to support MAML and operate in a distributed environment that permits sharing of agent development knowledge between various tools and tool instances. Tests of MAML and ARAMS with agent Tool are summarized, and related future work suggested.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Improved Feature Extraction, Feature Selection, and Identification Techniques That Create a Fast Unsupervised Hyperspectral Target Detection Algorithm
This research extends the emerging field of hyperspectral image (HSI) target detectors that assume a global linear mixture model (LMM) of HSI and employ independent component analysis (ICA) to unmix HSI images. Via new techniques to fully automate feature extraction, feature selection, and target pixel identification, an autonomous global anomaly detector, AutoGAD, has been developed for potential employment in an operational environment for real-time processing of HSI targets. For dimensionality reduction (initial feature extraction prior to ICA), a geometric solution that effectively approximates the number of distinct spectral signals is presented.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Realtime Color Stereovision Processing
Recent developments in aviation have made micro air vehicles (MAVs) a reality. These featherweight palm-sized radio-controlled flying saucers embody the future of air-to-ground combat. No one has ever successfully implemented an autonomous control system for MAVs. Because MAVs are physically small with limited energy supplies, video signals offer superiority over radar for navigational applications. This research takes a step forward in realtime machine vision processing. It investigates techniques for implementing a realtime stereovision processing system using two miniature color cameras. The effects of poor-quality optics are overcome by a robust algorithm, which operates in realtime and achieves frame rates up to 10 fps in ideal conditions. The vision system implements innovative work in the following five areas of vision processing: fast image registration preprocessing, object detection, feature correspondence, distortion-compensated ranging, and multiscale nominal frequency-based object recognition. Results indicate that the system can provide adequate obstacle avoidance feedback for autonomous vehicle control. However, typical relative position errors are about 10%--to high for surveillance applications. The range of operation is also limited to between 6 - 30m. The root of this limitation is imprecise feature correspondence: with perfect feature correspondence the range would extend to between 0.5 - 30m. Stereo camera separation limits the near range, while optical resolution limits the far range. Image frame sizes are 160x120 pixels. Increasing this size will improve far range characteristics but will also decrease frame rate.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Multi-Robot Fastslam for Large Domains
For a robot to build a map of its surrounding area it must have accurate position information within the area and to obtain the accurate position information within the area, the robot need to have an accurate map of the area. This circular problem is the Simultaneous Localization and Mapping (SLAM) problem. An efficient algorithm to solve it is FastSLAM, which is based on the Rao-Blackwellized particle filter. FastSLAM solves the SLAM problem for single-robot mapping using particles to represent the posterior of the robot pose and the map. Each particle of the filter possesses its own global map which is likely to be a grid map. The memory space required for these entire maps pose a serious limitation to the algorithm's capability when the problem space is large. In addition this problem will only get worse if the algorithm is adapted to a multirobot mapping. This thesis presents an alternate mapping algorithm that extends this single-robot FastSLAM algorithm to a multi-robot mapping algorithm that uses Absolute Space Representations to represent the world.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Coalition Formation Under Uncertainty
Many multiagent systems require allocation of agents to tasks in order to ensure successful task execution. Most systems that perform this allocation assume that the quantity of agents needed for a task is known beforehand. Coalition formation approaches relax this assumption, allowing multiple agents to be dynamically assigned. Unfortunately, many current approaches to coalition formation lack provisions for uncertainty. This prevents application of coalition formation techniques to complex domains, such as real-world robotic systems and agent domains where full state knowledge is not available. Those that do handle uncertainty have no ability to handle dynamic addition or removal of agents from the collective and they constrain the environment to limit the sources of uncertainty.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Power, Performance, and Perception (P3)
Currently, there are two distinct approaches to assist information technology managers in the successful implementation of office automation software. The first approach resides within the field of usability engineering, while the second approach is derived from the discipline of management information systems (MIS). The usability engineering approach has focused the question, "can users use the system?" while the MIS approach has answered the question, "will users use the system?" However, neither approach has successfully produced conclusive evidence that explains what characteristics facilitate system use as well as influence user acceptance of the system. This study reports on the validity of a new model, entitled the Power, Performance, Perception (P 3 ) model, that links the constructs of usability engineering to user acceptance. For this study, speech recognition software (SRS), selected as the target technology due to its novelty and practical application to office automation software, was used in an experimental setting to validate the P 3 model. As a secondary focus, this research also examined the viability of employing SRS in an Air Force office setting. The results of this study failed to validate the P 3 model. However, an alternate model for predicting user acceptance, the Usability-Acceptance Model, did emerge from the research which showed that the usability metric of user satisfaction can explain 53% of the variance of user intention to use a new technology. Additionally, the results of this study indicate that while users in a typical Air Force office environment would utilize SRS for text processing, the issue of increased productivity bears further examination.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Multiagent Systems Engineering
This thesis defines a methodology for the creation of multiagent systems, the Multiagent Systems Engineering (MaSE) methodology. The methodology is a key issue in the development of any complex system and there is currently no standard or widely used methodology in the realm of multiagent systems. MaSE to covers the entire software lifecycle, starting from an initial prose specification, and creating a set of formal design documents in a graphical style based on a formal syntax. The final product of MaSE is a diagram describing the deployment of a system of intelligent agents that communicate through structured conversations. MaSE was created with the intention of being supported an automated design tool. The tool built to support MaSE, agent Tool, is a multiagent system development tool for designing and synthesizing complex multiagent systems.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Social Networking Website Users and Privacy Concerns
Social networking websites are the fastest growing entity on the Internet. Users of social networking websites post personal information and pictures on these websites. Privacy and social networking websites has been previously studied, however, since those studies were conducted the rules for those websites have changed dramatically. A mixed methods approach was used in this study to examine what privacy concerns users of social networking websites have, whether it's regarding information on their accounts or the pictures they have posted. This study also considered if there were common personality traits present in people with those concerns. A comparison of user preferences between MySpace and Facebook was also conducted. Quantitative data in the form of survey information was used in addition to qualitative data gathered from semistructured interviews. This study supports that Social Desirability Bias was correlated with a user being selective of what pictures were displayed on social networking website accounts. Few users expressed a preference for one social networking website over the other. Over half of the participants did express concern for their privacy on social networking website accounts, but there were no personality factors that showed to be predictive of that concern.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Taking the High Ground
Cloud computing offers tremendous opportunities for private industry, governments, and even individuals to access massive amounts of computational resources on-demand at very low cost. Recent advancements in bandwidth availability, virtualization technologies, distributed programming paradigms, security services and general public awareness havecontributed to this new business model for employing information technology (IT) resources. IT managers face tough decisions as they attempt to balance the pros and cons of integrating commercial cloud computing into their existing IT architectures. On one hand, cloud computing provides on-demand scalability, reduces capital and operational expenses, decreases barriers to entry, and enables organizations to refocus on core competencies rather than on IT expertise.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
A Tabu Search Metaheuristic for the Air Refueling Tanker Assignment Problem
In a joint effort between Air Mobility Command (AMC) and the Air Force Institute of Technology, we present a Tanker Assignment Problem (TAI`) Tool capable of providing tanker mission plans for deployment scenarios. Due to the complex nature of extracting a mission plan from the Combined Mating and Ranging Planning System (CMARPS), AMC requires a tool to provide similar results in a simpler and less time consuming manner. The tool developed allows AMC to input several receiver groups consisting of various aircraft types and numbers. Each receiver group contains a point of origin and destination, with the option of providing one waypoint along the path. In addition, each group has a ready to load date (RLD) and required delivery date (RDD). The user is also able to specify the locations of military tanker aircraft. The main goal of this tool is to assign the tankers to the different refueling points of the receiver groups so that all receiver groups arrive before their RDD. Secondary goals include the reuse of tankers and limiting the total flight distance for all tanker aircraft. The TAP Tool uses the heuristic technique tabu search to determine an assignment of tankers to receiver groups during a deployment.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
A Monocular Vision Based Approach to Flocking
Flocking is seen in nature as a means for self protection, more efficient foraging, and other search behaviors. Although much research has been done regarding the application of this principle to autonomous vehicles, the majority of the research has relied on GPS information, broadcast communication, an omniscient central controller, or some other form of "global" knowledge. This approach, while effective, has serious drawbacks, especially regarding stealth, reliability, and biological grounding. This research effort uses three Pioneer P2-AT8 robots to achieve flocking behavior without the use of global knowledge. The sensory inputs are limited to two cameras, offset such that the area of stereo vision is minimal, thus making stereo image analysis techniques effectively impossible, but allowing a much larger effective field of vision. The flocking algorithm analyzes these images and updates each robot's velocity vector according to the relative position, heading, and speed of its nearest neighbor. The result of this velocity update is an eventual stabilization of speed and heading, resulting in a coherent, stable flock, demonstrated in both software simulation and in hardware.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Improved Multispectral Skin Detection and Its Application to Search Space Reduction for Dismount Detection Based on Histograms of Oriented Gradients
Due to the general shift from conventional warfare to terrorism and urban warfare by enemies of the United States in the late 20th Century, locating and tracking individuals of interest have become critically important. Dismount detection and tracking are vital to provide security and intelligence in both combat and homeland defense scenarios including base defense, combat search and rescue (CSAR), and border patrol. This thesis focuses on exploiting recent advances in skin detection research to reliably detect dismounts in a scene. To this end, a signal-plus-noise model is developed to map modeled skin spectra to the imaging response of an arbitrary sensor, enabling an in-depth exploration of multispectral features as they are encountered in the real world for improved skin detection. Knowledge of skin locations within an image is exploited to cue a robust dismount detection algorithm, significantly improving dismount detection performance and efficiencyThis work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Using Upper Layer Weights to Efficiently Construct and Train Feedforward Neural Networks Executing Backpropagation
Feed-forward neural networks executing back propagation are a common tool for regression and pattern recognition problems. These types of neural networks can adjust themselves to data without any prior knowledge of the input data. Feed-forward neural networks with a hidden layer can approximate any function with arbitrary accuracy. In this research, the upper layer weights of the neural network structure are used to determine an effective middle layer structure and when to terminate training. By combining these two techniques with signal-to-noise ratio feature selection, a process is created to construct an efficient neural network structure. The results of this research show that for data sets tested thus far, these methods yield efficient neural network structure in minimal training time. Data sets used include an XOR data set, Fisher's Iris problem, a financial industry data set, among others.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
The Generalizability of Private Sector Research on Software Project Management in Two USAF Organizations
Project managers typically set three success criteria for their projects: meet specifications, be on time, and be on budget. However, software projects frequently fail to meet these criteria. Software engineers, acquisition officers, and project managers have all studied this issue and made recommendations for achieving success. But most of this research in peer reviewed journals has focused on the private sector. Researchers have also identified software acquisitions as one of the major differences between the private sector and public sector MIS. This indicates that the elements for a successful software project in the public sector may be different from the private sector. Private sector project success depends on many elements. Three of them are user interaction with the project's development, critical success factors, and how the project manager prioritizes the traditional success criteria. High user interaction causes high customer satisfaction, even when the traditional success criteria are not completely met. Critical success factors are those factors a project manager must properly handle to avoid failure. And priorities influence which success criteria the project manager will most likely succeed in meeting.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.
Cloud Computing using Salesforce
Salesforce, as the leading cloud-based CRM platform, empowers businesses to manage customer relationships and build custom applications. This book serves as your comprehensive guide to mastering this technology, from foundational cloud concepts to advanced development and administration, enabling you to leverage its full potential.This book provides a structured journey, starting with cloud computing fundamentals and a thorough introduction to Salesforce, including its Lightning Platform architecture and benefits. This new edition brings in-depth coverage of Lightning Web Components (LWC), equipping you with the skills to build modern, high-performance user interfaces, aligning with the latest Salesforce development standards. Lastly, you will learn how to deploy and debug the app, with enhanced coverage on advanced Apex handlers for robust integrations and asynchronous processing. The book focuses on how to design an app. You will then learn how to use the Salesforce data process and security architecture in the app design and understand how to use force.com to customize the UI and automate the process. Lastly, you will learn practical debugging and deployment techniques.Upon completing this book, you will be highly competent in declarative and programmatic aspects of Salesforce, ready to confidently build, customize, and manage solutions, and prepared for official Salesforce Administrator, Platform App Builder, and Platform Developer I certifications.WHAT YOU WILL LEARN● Get an overview of Salesforce.● In this edition, learn more about the Lightning Experience unit.● Understand the design and data process.● Learn how to develop reports and dashboards in Salesforce.● Automate business process using Salesforce tools. ● ⁠Get familiar with the programming in Apex language.WHO THIS BOOK IS FORThis book is ideal for computer science students and Salesforce Admins looking to deepen their platform knowledge, especially in development. It is also perfect for professionals aiming to learn LWC and Salesforce Administrator, Platform App Builder or Platform Developer I certifications, assuming a basic understanding of computer concepts.
5000 Years of Science
What is science, really-and where is it taking us?In this sweeping journey across five millennia, 5000 Years of Science traces the rise of human understanding, from ancient Mesopotamian star charts to cutting-edge theories of artificial intelligence and quantum consciousness. This is not just a history of inventions and discoveries-it's a bold reinterpretation of science as the evolving expression of our deepest survival instincts, cognitive tools, and existential questions.Explore how early civilisations laid the mathematical and astronomical foundations of science. Witness the intellectual explosions of the Scientific Renaissance and Enlightenment. Follow the dramatic revolutions of chemistry, physics, biology, and computing. And then step into the future-with explorations of AI, neuroscience, quantum biology, and the search for a unified theory of consciousness.A Journey Through Human Discovery - and a Radical New Idea That May Change Everything We Know About the MindWhat if consciousness isn't a mystery... but an evolved tool for survival?In this bold and sweeping book, 5000 Years of Science traces the story of human discovery-from the fires of early civilisation to the quantum codes of artificial intelligence. With every chapter, the reader journeys through astronomy, biology, physics, and psychology-culminating in a groundbreaking theory that redefines what it means to be conscious.Introducing Affective Survival Theory (AST)-a new scientific framework that argues feeling is not a byproduct of thought, but the engine of survival. Pain, pleasure, fear, hunger, love: these are not abstract states, but evolution's way of tagging experience with meaning. From the reflex of a single cell to the awe of cosmic wonder, AST reveals how consciousness evolved not to think first-but to feel and adapt.���� Inside This Book: The 5000-year timeline of science, from ancient astronomy to AIThe rise of artificial intelligence and the limits of machine mindsWhy consciousness evolved through emotionally charged survivalHow AST compares to other leading theories (IIT, GWT, Orch OR, etc.)A reframe of the hard problem of consciousness into the hard advantage of feelingThe emotional roots of memory, imagination, reasoning, and transcendenceWhether you're a science lover, philosopher, futurist, or simply curious about the nature of the mind, 5000 Years of Science will challenge your assumptions, ignite your curiosity, and change how you see yourself-and consciousness itself.This is more than a book. It's the next chapter in the human story.
The Dharma of AI
You just glanced at your phone, didn't you? That's exactly how algorithms draw us in. We're living suspended between two worlds: one where AI quietly decides who gets hired, what news we see, and which voices we hear--and another where millennia of human wisdom sit waiting to guide us.After forty years building AI systems and twenty years studying dharma in Indian ashrams, author Alok R. Chaturvedi learned something crucial: our digital future desperately needs our philosophical past. This isn't another robot apocalypse book--it is an invitation to see technology through ancient wisdom made urgently relevant as artificial general intelligence approaches. Through deeply human stories--a coder discovering her biases embedded in "neutral" algorithms, a parent watching their child disappear into endless scrolling--we explore how technology impacts us across three dimensions: Daihik (personal), Daivik (universal), and Bhautik (material). We also examine how technology carries the Three Gunas: Sattvik (clarity), Rajasik (restlessness), and Tamsik (numbness). Additionally, The Dharma of AI introduces the Five Guardians, which are timeless ethical principles: Ahimsa (do no harm), Satya (seek truth), Asteya (take only what's given), Brahmacharya (consume mindfully), and Dharma (act righteously). Whether building technology, raising children, or seeking authentic digital living, this book offers profound insight and practical wisdom for our most urgent conversation.
Artificial Intelligence in Education
This six-volume set LNAI 15877-15882 constitutes the refereed proceedings of the 26th International Conference on Artificial Intelligence in Education, AIED 2025, held in Palermo, Italy, during July 22-26, 2025. The 130 full papers and 129 short papers presented in this book were carefully reviewed and selected from 711 submissions. The conference program comprises seven thematic tracks: Track 1: AIED Architectures and Tools Track 2: Machine Learning and Generative AI: Emphasising datadrivenTrack 3: Learning, Teaching, and Pedagogy Track 4: Human-Centred Design and Design-Based Research Track 5: Teaching AI Track 6: Ethics, Equity, and AIED in Society Track 7: Theoretical Aspects of AIED and AI-Based Modelling forEducation
Artificial Intelligence in Education
This six-volume set LNAI 15877-15882 constitutes the refereed proceedings of the 26th International Conference on Artificial Intelligence in Education, AIED 2025, held in Palermo, Italy, during July 22-26, 2025. The 130 full papers and 129 short papers presented in this book were carefully reviewed and selected from 711 submissions. The conference program comprises seven thematic tracks: Track 1: AIED Architectures and Tools Track 2: Machine Learning and Generative AI: Emphasising datadrivenTrack 3: Learning, Teaching, and Pedagogy Track 4: Human-Centred Design and Design-Based Research Track 5: Teaching AI Track 6: Ethics, Equity, and AIED in Society Track 7: Theoretical Aspects of AIED and AI-Based Modelling forEducation
Neural Information Processing
The sixteen-volume set, CCIS 2282-2297, constitutes the refereed proceedings of the 31st International Conference on Neural Information Processing, ICONIP 2024, held in Auckland, New Zealand, in December 2024. The 472 regular papers presented in this proceedings set were carefully reviewed and selected from 1301 submissions. These papers primarily focus on the following areas: Theory and algorithms; Cognitive neurosciences; Human-centered computing; and Applications.
Applied Artificial Intelligence 4: Medicine, Biology, Chemistry, Financial, Games, Engineering
The book covers the state-of-the-art research knowledge and results on the innovative theories, methodology and applications of artificial intelligence and its sub-domain like deep learning in different areas such as medicine, economy, education, law, smart city, government, industry etc. Moreover, the book aims to provide a platform for researchers and practitioners for both academia and industry to share the information about cutting-edge developments in the field of artificial intelligence. The chapters in this book integrated approach toward global exchange of information on technological advances, scientific innovations and the effectiveness of various regulatory programs toward AI application in medicine, biology, chemistry, financial, games, law and engineering. Real examples from academia and industry give beyond state of the art for application of AI in different areas. These chapters are extended papers from the Third Serbian International Conference on Applied Artificial Intelligence (SICAAI), which was held in Kragujevac, Serbia, on May 23-24, 2024.
Transformative Museum Experiences
Following on the volume Museum Experience Design (2018), this book acknowledges the changing role of museums in society with a focus on designing experiences as vehicles for transformation. We look at transformation through a systemic perspective, anchored in the experience that museums offer to visitors. One facet of our exploration regards the museum experience itself as an instrument for change. At this level we conceptualise what we mean by a transformative experience and look at design approaches specifically geared towards inducing transformation. We then turn attention towards the way recent changes in the socio-political and cultural context reverberated in structural and functional changes inside the museum and connected institutions and communities, with shifting museum identities and new forms of cooperation emerging. Finally, we zoom in on the role of technology in the making of transformative museum experiences, looking at opportunities and affordances but also calling for an ethical approach to integration of technology in museum practice.
AI on the Frontlines
The emergence of Artificial Intelligence (AI) has drastically altered the conditions of warfare. AI now plays an integral role in every facet of a nation-state's military/surveillance structure, from cybersecurity to espionage to covert operations. AI technologies are reshaping the science of cyber warfare. A single slip could mean dire consequences with the new world order where AI technologies have become mainstream not just for nation states but organisations as well. For organisation and state-sponsored alike, the associated risk grows ever higher against stakes that have outpaced sophistication which can be claimed to be unprecedented. This book outlines the new standards where deep learning, automated reasoning, and advanced algorithms have created new frontiers on offence and defence in digital warfare. A single error in enterprise security could lead to the downfall of a business. Exceeding malware threats and recovering inside jobs have become trivially easy now AI powered programmes have taken the wheel. AI systems can execute actions at lightning speeds allowing business alongside governments to carry out covert operations without breaking a sweat. A powerful pioneer such as AI comes with risks that do not only end at the sidelines. Offensively, AI can now be applied to autonomously run social engineering schemes through swiftly mobilisable global bots that rapidly span across borders. These nodes come armed with advanced features like adaptive maneuvers and evasion protocols, allowing them to adapt the information they feed to infiltrator malware all while dodging identifiers and making undetectable changes in real time. In a world superseded by advanced technologies, one does not simply remain undetected.By using practical examples and future-focused studies, the book explores how AI can act as both a protective shield and a sword. Most importantly, the book does not act as a mere technical guide. It analyses the social, legal, and political consequences of AI cyber-power strategies. What constitutes permissible boundaries of electronic warfare? How do global treaties cope with autonomous strategy algorithms for attacking? In an AI-enabled warfare, where does human accountability start and stop? It is intended for practitioners in security, IT executives, scholars, and other concerned citizens who wish to engage with the future of digital technology. This book untangles the complicated theories and concepts of modern cyber defence and offence, equipping readers to deal with these challenges in the future. If you are looking for protective strategies for your organisation, or want to understand emerging cyber threats, Cyber Defence and Offensive AI Strategies offers an authoritative yet balanced take on the global intelligence competition that is urgently reshaping the world's digital infrastructure.This text will be highly useful for cybersecurity practitioners, IT managers, penetration testers, and threat intelligence analysts looking to familiarise themselves with the new dimensions of AI technology in both defence and offence of cyber domains. Security architects and CISOs will find relevant actionable strategies on use of AI in their defensive strategies, while educators, students, and researchers in computer science and security studies will find a thorough contemporary reference. Besides, policymakers, lawyers, and ethical commentators concerned with the social consequences of autonomous cyber operations would be interested in the book's discussions on regulation and the limits of warfare in cyberspace. It doesn't matter whether you are a seasoned authority, an emerging professional, or simply someone who cares about the evolution of digital security. This book is a must-read for you.
Advanced Intelligent Computing Technology and Applications
The 12-volume set CCIS 2564-2575, together with the 28-volume set LNCS/LNAI/LNBI 15842-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The 523 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".
Artificial Intelligence in Education
This six-volume set LNAI 15877-15882 constitutes the refereed proceedings of the 26th International Conference on Artificial Intelligence in Education, AIED 2025, held in Palermo, Italy, during July 22-26, 2025. The 130 full papers and 129 short papers presented in this book were carefully reviewed and selected from 711 submissions. The conference program comprises seven thematic tracks: Track 1: AIED Architectures and Tools Track 2: Machine Learning and Generative AI: Emphasising datadrivenTrack 3: Learning, Teaching, and Pedagogy Track 4: Human-Centred Design and Design-Based Research Track 5: Teaching AI Track 6: Ethics, Equity, and AIED in Society Track 7: Theoretical Aspects of AIED and AI-Based Modelling forEducation
Advanced Intelligent Computing Technology and Applications
The 20-volume set LNCS 15842-15861, together with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869, constitutes the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The 1206 papers presented in these proceedings books were carefully reviewed and selected from 4032 submissions. They deal with emerging and challenging topics in artificial intelligence, machine learning, pattern recognition, bioinformatics, and computational biology.
Medical Image Understanding and Analysis
The three-volume set LNCS 15916,15917 & 15918 constitutes the refereed proceedings of the 29th Annual Conference on Medical Image Understanding and Analysis, MIUA 2025, held in Leeds, UK, during July 15-17, 2025. The 67 revised full papers presented in these proceedings were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: Part I: Frontiers in Computational Pathology; and Image Synthesis and Generative Artificial Intelligence. Part II: Image-guided Diagnosis; and Image-guided Intervention. Part III: Medical Image Segmentation; and Retinal and Vascular Image Analysis.
Advanced Intelligent Computing Technology and Applications
This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The total of 1206 regular papers were carefully reviewed and selected from 4032 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".
Azure AI-102 Certification Essentials
Go beyond AI-102 certification by mastering the foundations of Azure AI concepts and services-reinforced through practical labs and real-world examples.Key Features: - Solidify your understanding with targeted questions at the end of each chapter- Assess your knowledge of key concepts with over 45 exam-style questions, complete with detailed explanations- Get hands-on experience with GitHub projects, along with ongoing support from the author on GitHub- Purchase of the print or Kindle book includes a free PDF eBookBook Description: Written by a seasoned solutions architect and Microsoft AI professional with over 25 years of IT experience, Azure AI-102 Certification Essentials will help you gain the skills and knowledge needed to confidently pass the Azure AI-102 certification exam and advance your career. This comprehensive guide covers all of the exam objectives, from designing AI solutions to integrating AI models into Azure services. By combining theoretical concepts with visual examples, hands-on exercises, and real-world use cases, the chapters teach you how to effectively apply your new-found knowledge.The book emphasizes responsible AI practices, addressing fairness, reliability, privacy, and security, while guiding you through testing AI models with diverse data and navigating legal considerations. Featuring the latest Azure AI tools and technologies, each chapter concludes with hands-on exercises to reinforce your learning, culminating in Chapter 11's comprehensive set of 45 mock questions that simulate the actual exam and help you assess your exam readiness.By the end of this book, you'll be able to confidently design, implement, and integrate AI solutions on Azure, while achieving this highly sought-after certification.What You Will Learn: - Learn core concepts relating to AI, LLMs, NLP, and generative AI- Build and deploy with Azure AI Foundry, CI/CD, and containers- Manage and secure Azure AI services with built-in tools- Apply responsible AI using Azure AI Content Safety- Perform OCR and analysis with Azure AI Vision- Build apps with the Azure AI Language and Speech services- Explore knowledge mining with Azure AI Search and Content Understanding- Implement RAG and fine-tuning with Azure OpenAI- Build agents using Azure AI Foundry Agent Service and Semantic KernelWho this book is for: If you're preparing for the Azure AI-102 certification exam, this book is for you. Developers, engineers, and career transitioners moving from traditional software development to AI-focused roles can use this guide to deepen their understanding of AI within the Azure ecosystem. This book is also beneficial for students and educators looking to apply AI/ML concepts using Azure. No prior experience in AI/ML is required as this book provides comprehensive coverage of exam topics with detailed explanations, practical examples, and hands-on exercises to build your confidence and expertise.Table of Contents- Understanding AI, ML, and Azure's AI Services- Getting Started with Azure AI: Studio, Pipelines, and Containerization- Managing, Monitoring, and Securing Azure AI Services- Implementing Content Moderation Solutions- Exploring Azure AI Vision Solutions- Implementing Natural Language Processing Solutions- Implementing Knowledge Mining, Document Intelligence, and Content Understanding- Working on Generative AI Solutions- Implementing Agentic Solutions with Azure AI Agent Service- Practical AI Implementation: Industry Use Cases, Technical Patterns, and Hands-On Projects- Preparing for the AI-102: Azure AI Engineer Associate Certification Exam
Agent AI for Finance
This open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors' thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a previous book, "From Opinion Mining to Financial Argument Mining" (Springer, 2021), the first author discussed understanding financial documents in a fine-grained manner, particularly those containing opinions. The book highlighted several future directions, such as financial argument mining, multimodal opinion understanding, and analysis generation, and anticipated a lengthy journey for these topics. However, since 2022, ChatGPT and large language models (LLMs) have shown promising advancements, motivating the authors to write this second book on the topic of financial Natural Language Processing (NLP). Agent-based AI systems have been widely discussed since the advent of LLMs. This book aims to equip researchers and practitioners with the latest methodologies, concepts, and frameworks for developing, deploying, and evaluating AI agents with capabilities in multimodal understanding, decision-making, and interaction. It places a special emphasis on human-centered decision-making and multi-agent cooperation in financial applications. The book surveys the current landscape and discuss future research and development directions. Targeting a wide audience, from students to seasoned researchers in AI and finance, this book offers an overview of recent trends in Agent AI for finance. It provides a foundation for students to understand the field and design their research direction, while inviting experienced researchers to engage in discussions on open research questions informed by pilot experimental results. Although this book focuses on financial applications, the discussed concepts and methods can also be applied to other real-world applications by integrating domain-specific characteristics. The authors look forward to seeing new findings and more novel extensions based on the proposed ideas.
The fanatics
Step into a world where humor meets humanity in "The Fanatics: A Comedy in Three Acts," a captivating play that has been out of print for decades and is now lovingly republished by Alpha Editions. This restored edition not only revives a classic but transforms it into a collector s item and a cultural treasure for today s and future generations. At the heart of this engaging narrative lies a satirical exploration of obsession and fanaticism, delivered through witty dialogue and a character-driven storyline that keeps audiences laughing and reflecting. As you follow the eccentric characters on their comedic journey, you'll discover a vibrant tapestry of modern comedy that resonates with the timeless struggles of the human spirit. "The Fanatics" is more than just a play; it s a celebration of theatrical comedy that invites both casual readers and classic literature collectors to immerse themselves in its rich, humorous landscape. With its unique blend of satire and engaging dialogue, this work stands as a testament to the enduring power of laughter in literature. Don t miss your chance to own this remarkable piece of theatrical history. Perfect for comedy enthusiasts and those who appreciate the art of stage performance, "The Fanatics" is a must-have addition to any bookshelf. Embrace the joy of classic literature with this restored gem, and let its humor inspire you anew!
AI Needs You
A humanist manifesto for the age of AI Artificial intelligence may be the most transformative technology of our time. As AI's power grows, so does the need to figure out what--and who--this technology is really for. AI Needs You argues that it is critical for society to take the lead in answering this urgent question and ensuring that AI fulfills its promise. Verity Harding draws inspiring lessons from the histories of three twentieth-century tech revolutions--the space race, in vitro fertilization, and the internet--to empower each of us to join the conversation about AI and its possible futures. Sharing her perspective as a leading insider in technology and politics, she rejects the dominant narrative, which often likens AI's advent to that of the atomic bomb. History points the way to an achievable future in which democratically determined values guide AI to be peaceful in its intent; to embrace limitations; to serve purpose, not profit; and to be firmly rooted in societal trust. Now with a new foreword by the author, AI Needs You gives us hope that we, the people, can imbue AI with a deep intentionality that reflects our best values, ideals, and interests, and that serves the public good. AI will permeate our lives in unforeseeable ways, but it is clear that the shape of AI's future--and of our own--cannot be left only to those building it. It is up to us to guide this technology away from our worst fears and toward a future that we can trust and believe in.
Advanced Distributed Scrum
Master distributed Scrum with real-world strategies and tools such as Slack, Trello, and CI/CD platforms to lead, collaborate, and deliver high-performing Agile projects, no matter where your team is locatedKey Features: - Help your team succeed globally while staying grounded in Agile Values and the 2020 Scrum Guide- Bridge async and sync work to increase alignment and team accountability- Apply real-world strategies for leading high-performing distributed teams- Purchase of the print or Kindle book includes a free PDF eBookBook Description: The COVID-19 pandemic altered the way teams work, turning remote work into a common practice for Agile teams that were originally founded to be co-located, leaving teams to grapple with remote and hybrid setups. The Agile mindset, however, remains the standard for effective teamwork, and this book integrates distributed work into your Agile and Scrum Values. Advanced Distributed Scrum will guide you in harnessing the talents of global team members and overcoming the challenges of working across geographies.Renowned Agile coach and educator Kelley O'Connell distills 25+ years of experience into this concise guide. The book begins by establishing the foundational principles of distributed Scrum, highlighting the unique roles and responsibilities within hybrid and remote environments. You'll gain insights into the challenges faced by distributed Agile teams and explore how to cultivate a strong remote team culture, improve communication, and effectively manage conflicts in a virtual space. Finally, you'll put remote Scrum practices into action to maximize the outcomes you're aiming for.By the end of this book, you'll be equipped to lead and nurture high-performing distributed teams, facilitate remote ceremonies, implement remote-friendly CI/CD pipelines, and create team norms that drive engagement.What You Will Learn: - Define and align remote roles for seamless collaboration- Set up tools, workspaces, and team agreements for success- Recruit, onboard, and integrate remote team members- Build a strong team culture and resolve conflicts remotely- Facilitate remote Scrum events across time zones- Implement CI/CD pipelines in distributed environments- Ensure security and compliance in remote Scrum setupsWho this book is for: This book is for Scrum Masters, Agile practitioners, coaches, product owners, and team leads who want to master remote and hybrid collaboration and build high-performing distributed Scrum teams. Whether you're experienced or new to leading distributed teams, this practical guide offers tools to enhance team effectiveness and continuous collaboration. A foundational understanding of Agile principles, the Agile mindset, and core frameworks is recommended to get the most value from this book.Table of Contents- Introduction to Agile and Scrum- Principles of Distributed Scrum- Roles and Responsibilities in a Distributed Scrum Team- Setting Up for Remote Scrum Success- Recruiting and Forming a Distributed Scrum Team- Cultivating a Strong Remote Culture- Effective Communication and Working Agreements- Collaboration and Tools and Software- Collaboration Tools and Software- Remote Pair Programming and Code Reviews- Continuous Integration and Continuous Deployment (CI/CD)- Security and Compliance in Remote Work- Remote Sprint Planning- Conducting a Distributed Daily Scrum- Sprint Execution and Monitoring- Sprint Review and Retrospective
Artificial Intelligence and Machine Learning
This CCIS volume constitutes the refereed proceedings of Second International Artificial Intelligence Conference on Artificial Intelligence and Machine Learning, IAIC 2024, held in Jinyun, China, November 2024. The 38 full papers presented were carefully reviewed and selected from 100 submissions.They were organized in following topical sections as follows: Part I: Artificial Intelligence in Real-World Applications.Part II: Artificial Intelligence in Network and Security systems.
Cloud Computing & Big Data Tech (2nd Ed)
This book comprehensively introduces the basic knowledge and main technologies of cloud computing and big data. It covers cloud computing, big data technology, virtualization technology, data centers, parallel computing and clustering technology, cloud storage technology, OpenStack, Hadoop, Spark, Storm, and cloud computing simulation.With a focus on practicality, this volume is enriched with experiments and closely integrates theory with practice, enabling readers to systematically and comprehensively understand cloud computing and big data technologies.This useful reference textbook benefits professionals, academics, researchers, graduate and undergraduate students in databases/information sciences.
Detecting Online Propaganda and Misinformation
This unique compendium provides a comprehensive overview of the state-of-the-art methods in the extremely 'hot' area of online propaganda detection and monitoring. It discusses the difficulties of developing automated methods and systems for online propaganda and misinformation detection, along with the potential contributions of machine learning techniques.The presented methods are built upon the latest AI and Natural Language Processing technologies. Case studies refer to recent events such as the COVID-19 pandemic and the Russian-Ukrainian military conflict.This useful reference text benefits academics, researchers, professionals and graduate students in AI, NLP, machine learning and information sciences.
Advanced Intelligent Computing Technology and Applications
This 20-volume set LNCS 15842-15861 constitutes - in conjunction with the 4-volume set LNAI 15862-15865 and the 4-volume set LNBI 15866-15869 - the refereed proceedings of the 21st International Conference on Intelligent Computing, ICIC 2025, held in Ningbo, China, during July 26-29, 2025. The total of 1206 regular papers were carefully reviewed and selected from 4032 submissions. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications".
