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Today, everything is marketing. All of the content we produce affects the customer experience. Therefore, all content is marketing and all content producers are marketers. Intelligent Content: A Primer introduces intelligent content: how it works, the benefits, the objectives, the challenges, and how to get started. Anyone who wants to understand intelligent content will get a clear introduction along with case studies and all the reference information you could ask for to make the case for intelligent content with your management. Intelligent Content: A Primer is written by three leaders in content strategy and content marketing. Ann Rockley is widely recognized as the mother of content strategy. Charles Cooper, co-author with Ann Rockley of Managing Enterprise Content, has been been involved in creating and testing digital content for more than 20 years. And Scott Abel, known as The Content Wrangler, is an internationally recognized global content strategist. Together, they have created the definitive introduction to intelligent content.

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MadCap Flare for Programmers shows how Flare manages and parses content and how you can interact with Flare outside the user interface. It introduces the structure of Flare content files and Flare output files, such as HTML5 help, and shows how you can manipulate those files. With more than 50 examples in languages such as JavaScript, C#, Java, XSLT, and Visual Basic, this book covers most of the ways you can programmatically interact with MadCap Flare. This book is for programmers who support Flare, technical writers who want to look under the hood, and managers who would like to know what possibilities exist beyond the Flare UI.

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All companies, no matter what industry they are in, or what product or service they create, do four basic things. Offer something for sale, sell it, collect money for it, and create content about what they do. Product development, Marketing, Sales, and Finance are all essential to the organization and are typically managed at the VP or CXO level, yet a company's content, which contains all of its intellectual property, is often overlooked. The Content Pool: Leveraging Your Company's Largest Hidden Asset makes the case for placing content creation, management, and distribution on a par with other core strategic business activities. Inside the Book Identifying Your ContentOrganizing Your ContentManaging Your ContentLeveraging Your ContentThe Case for a Chief Content OfficerBibliography and Index

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The Secret Life of Word looks at Microsoft Word from the perspective of technical and other professional writers. It gives writers an in-depth look at the hidden capabilities of Word, and shows how to take advantage of those capabilities without being a programmer. The Secret Life of Word will help you master the full gamut of Word mysteries, including AutoCorrect, QuickParts, BuildingBlocks, macros, Smart Tags, program-less VBA programming, and much more. There's something here for everyone who uses Microsoft Word, from new users to experts. Inside the Book PrefaceIntroduction to Word AutomationCreating MacrosFind and ReplaceFields, Form Fields, and Content ControlsAutoCorrect and AutoText/Building BlocksSmart TagsExchanging DataCode SamplesAutomation Related TopicsGlossary, Bibliography, and Index

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Written by world-renowned authors, this unique compendium presents the most updated progress in pattern recognition and computer vision (PRCV), fully reflecting the strong international research interests in the artificial intelligence arena. Machine learning has been the key to current developments in PRCV. This useful comprehensive volume complements the previous five editions of the book. It places great emphasis on the use of deep learning in many aspects of PRCV applications, not readily available in other reference text. Contents: Theory, Technology and Systems: A Brief Introduction to Part 1 (C H Chen) Optimal Statistical Classification (Edward R Dougherty, Jr and Lori Dalton) Deep Discriminative Feature Learning Method for Object Recognition (Weiwei Shi and Yihong Gong) Deep Learning Based Background Subtraction: A Systematic Survey (Jhony H Giraldo, Huu Ton Le, and Thierry Bouwmans) Similarity Domains Network for Modeling Shapes and Extracting Skeletons without Large Datasets (Sedat Ozer) On Curvelet-Based Texture Features for Pattern Classification (Reprinted from Chapter 1.7 of 5th HBPRCV) (Ching-Chung Li and Wen-Chyi Lin) An Overview of Efficient Deep Learning on Embedded Systems (Xianju Wang) Random Forest for Dissimilarity-Based Multi-View Learning (Simon Bernard, Hongliu Cao, Robert Sabourin, and Laurent Heutte) A Review of Image Colourisation (Bo Li, Yu-Kun Lai, and Paul L Rosin) Recent Progress of Deep learning for Speech Recognition (Jinyu Li and Dong Yu) Applications: A Brief Introduction to Part 2 (C H Chen) Machine Learning in Remote Sensing (Ronny Hänsch) Hyperspectral and Spatially Adaptive Unmixing for Analytical Reconstruction of Fraction Surfaces from Data with Corrupt Pixels (Fadi Kizel and Jon Atli Benediktsson) Image Processing for Sea Ice Parameter Identification from Visual Images (Qin Zhang) Applications of Deep Learning to Brain Segmentation and Labeling of MRI Brain Structures (Evan Fletcher and Alexander Knaack) Automatic Segmentation of IVUS Images Based on Temporal Texture Analysis (A Gangidi and C H Chen) Deep Learning for Historical Document Analysis (Foteini Simistira Liwicki and Marcus Liwicki) Signature Verification via Graph-Based Methods (Paul Maergner, Kaspar Riesen, Rolf Ingold, and Andreas Fischer) Cellular Neural Network for Seismic Pattern Recognition (Kou-Yuan Huang and Wen-Hsuan Hsieh) Incorporating Facial Attributes in Cross-modal Face Verification and Synthesis (Hadi Kazemi, Seyed Mehdi Iranmanesh, and Nasser M Nasrabadi) Connected and Autonomous Vehicles in the Deep Learning Era: A Case Study on Computer-Guided Steering (Rodolfo Valientea, Mahdi Zamana, Yaser P Fallaha, and Sedat Ozer) Readership: Graduate students, academics, practitioners, researchers, computer scientists, electrical and medical engineers.Deep Learning;Statistical Pattern Recognition;Random Forest Classification;Machine Learning;Image Colorization;Document Analysis;Seismic Recognition;Face Recognition;Remote Sensing;Medical Imaging00

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Multi-objective optimization problems (MOPs) and uncertain optimization problems (UOPs) which widely exist in real life are challengeable problems in the fields of decision making, system designing, and scheduling, amongst others. Decomposition exploits the ideas of ÔÇÿmaking things simpleÔÇÖ and ÔÇÿdivide and conquerÔÇÖ to transform a complex problem into a series of simple ones with the aim of reducing the computational complexity. In order to tackle the abovementioned two types of complicated optimization problems, this book introduces the decomposition strategy and conducts a systematic study to perfect the usage of decomposition in the field of multi-objective optimization, and extend the usage of decomposition in the field of uncertain optimization.<b>Contents:</b> <ul><li>Introduction</li><li>Decomposition-based Multi-objective Evolutionary Algorithm with the &#x03B5;-Constraint Framework</li><li>Decomposition-based Many-objective Evolutionary Algorithm with the &#x03B5;-Constraint Framework</li><li>An <i>A Posteriori</i> Decision-making Framework and Subproblems Co-solving Evolutionary Algorithm for Uncertain Optimization</li><li>Noise-Tolerant Techniques for Decomposition-based Multi-objective Evolutionary Algorithms</li><li>The Bi-objective Critical Node Detection Problem with Minimum Pairwise Connectivity and Cost: Theory and Algorithms</li><li>Solving Bi-objective Uncertain Stochastic Resource Allocation Problems by the CVaR-based Risk Measure and Decomposition-based Multi-objective Evolutionary Algorithms</li></ul><br><b>Readership:</b> Researchers and professionals in computer science that specialise or deal with multi-objective optimization and uncertain optimization in decision making, system designing, and scheduling.Algorithm Design;Application of Multi-Objective Uncertain Optimization Approaches;Multi-Objective Optimization;Uncertain Optimization;Combinatorial Optimization;Intelligent/Evolutionary Algorithms0<b>Key Features:</b><ul><li>Algorithm design</li><li>Application of multi-objective uncertain optimization approaches</li></ul>

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Congratulations on your decision to venture into the world of programming. Treat this quick study guide as your companion in your learning process. The information here is all you need to create your first HTML language program. From here, you can begin to create complex programs. It is important that you always keep a copy because even professionals need refreshers too!

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Algorithmic information theory (AIT), or Kolmogorov complexity as it is known to mathematicians, can provide a useful tool for scientists to look at natural systems, however, some critical conceptual issues need to be understood and the advances already made collated and put in a form accessible to scientists. This book has been written in the hope that readers will be able to absorb the key ideas behind AIT so that they are in a better position to access the mathematical developments and to apply the ideas to their own areas of interest. The theoretical underpinning of AIT is outlined in the earlier chapters, while later chapters focus on the applications, drawing attention to the thermodynamic commonality between ordered physical systems such as the alignment of magnetic spins, the maintenance of a laser distant from equilibrium, and ordered living systems such as bacterial systems, an ecology, and an economy. Key Features Presents a mathematically complex subject in language accessible to scientists Provides rich insights into modelling far-from-equilibrium systems Emphasises applications across range of fields, including physics, biology and econophysics Empowers scientists to apply these mathematical tools to their own research

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Microsoft Excel has a huge variety of formulas for a variety of situations, and most of them are fairly complex to use. An Excel 2013 Formulas study guide gives the user access to most or all of those formulas in a quick and easy manner. Instead of having to search the internet or flip through a large book, the user can simply find the categorized formula in the study guide and apply it with the tips given. A study guide organizes the formulas in an intuitive format and can easily be kept near the computer for convenient reference any time.

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A Microsoft Excel formulas study guide helps students by providing them with all of the formulas needed to perform tasks in Microsoft Excel in one convenient location. Any students taking an Information Systems or Information Technology class for business majors would find this kind of study guide useful. Most of the formulas used in Excel have to be found in various pages of the program's help section, so they are not in one place. Having the formulas all on one page provides students with a handy resource for looking up formulas without having to go through several tabs or flip through several pages of a book.

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