Bo Wang

This book documents the latest research progress in MOF/COF-polymer hybrid materials and reviews and summarises hybridization strategies to achieve MOF/COF polymeric composites.

Hybrid Metal-Organic Framework and Covalent Organic Framework Polymers

Feng Wang

Shubham Saboo

Cristian Mitroi

Susana Guzman

Implement neural search systems on the cloud by leveraging Jina design patterns Key FeaturesIdentify the different search techniques and discover applications of neural searchGain a solid understanding of vector representation and apply your knowledge in neural searchUnlock deeper levels of knowledge of Jina for neural searchBook Description Search is a big and ever-growing part of the tech ecosystem. Traditional search, however, has limitations that are hard to overcome because of the way it is designed. Neural search is a novel approach that uses the power of machine learning to retrieve information using vector embeddings as first-class citizens, opening up new possibilities of improving the results obtained through traditional search. Although neural search is a powerful tool, it is new and finetuning it can be tedious as it requires you to understand the several components on which it relies. Jina fills this gap by providing an infrastructure that reduces the time and complexity involved in creating deep learning–powered search engines. This book will enable you to learn the fundamentals of neural networks for neural search, its strengths and weaknesses, as well as how to use Jina to build a search engine. With the help of step-by-step explanations, practical examples, and self-assessment questions, you'll become well-versed with the basics of neural search and core Jina concepts, and learn to apply this knowledge to build your own search engine. By the end of this deep learning book, you'll be able to make the most of Jina's neural search design patterns to build an end-to-end search solution for any modality. What you will learnUnderstand how neural search and legacy search workGrasp the machine learning and math fundamentals needed for neural searchGet to grips with the foundation of vector representationExplore the basic components of JinaAnalyze search systems with different modalitiesUncover the capabilities of Jina with the help of practical examplesWho this book is for If you are a machine learning, deep learning, or artificial intelligence engineer interested in building a search system of any kind (text, QA, image, audio, PDF, 3D models, or others) using modern software architecture, this book is for you. This book is perfect for Python engineers who are interested in building a search system of any kind using state-of-the-art deep learning techniques.

Build deep learning–powered search systems that you can deploy and manage with ease

Neural Search - From Prototype to Production with Jina

Peng Zhang

Le Sun

Yuexian Hou

Jian-Yun Nie

This book constitutes the refereed proceedings of the 8th Information Retrieval Societies Conference, AIRS 2012, held in Tianjin, China, in December 2012. The 22 full papers and 26 poster presentations included in this volume were carefully reviewed and selected from 77 submissions. They are organized in topical sections named: IR models; evaluation and user studies; NLP for IR; machine learning and data mining; social media; IR applications; multimedia IT and indexing; collaborative and federated search; and the poster session.

8th Asia Information Retrieval Societies Conference, AIRS 2012, Tianjin, China, December 17-19, 2012, Proceedings

Information Retrieval Technology

Matthew He

Zhengbing Hu

Sergey Petoukhov

This book includes refereed papers presented at the Second International Conference on Artificial Intelligence and Power Engineering (AIPE2021), which was held in Moscow, Russia, on December 17–19, 2021. The general scope of the book includes the most recent advances in the development of artificial intelligence systems and their applications in a variety of fields, ranging from power engineering to biology and education. Given the rapid development of artificial intelligence systems, the book emphasizes the importance of intensifying training for a growing number of relevant specialists, particularly in energy and power engineering, in order to improve the effectiveness of the creation and diagnosis of appropriate technical solutions. Scientists are attempting to replicate the innate intellectual abilities of humans and other organisms in digital artificial intelligence systems. In-depth research into biological and self-organizing systems can provide new approaches for developing more and more effective artificial intelligence methods. The papers included in this volume cover thematic materials in the following areas: mathematics and computer algorithms; analysis of some technical solutions; and technological and educational approaches. The book is a collection of cutting-edge papers in the field, covering a wide range of topics relevant to both business managers and engineering professionals. These proceedings are an excellent resource for asset management practitioners, researchers, and academics, as well as undergraduate and postgraduate students interested in artificial intelligence systems and their expanding applications, due to their breadth and depth. The intended readership includes specialists, students, and other groups of readers who want to know where artificial intelligence systems can be used to great advantage in the future.

Advances in Artificial Systems for Power Engineering II

Xiangsheng Liu

Yaqi Zhang

The book focuses on the Internet of Things and Beidou system application. Both principles and engineering practice have been addressed, with more weight placed on engineering practice. This is achieved by providing in-depth studies on a number of major topics of Beidou system application with the Internet of Things. Such comprehensive and systematic analysis is particularly suited for readers who are interested to learn practical solutions in Beidou system application. The book can benefit researchers, engineers, and graduate students in the fields of positioning and navigation, geospatial engineering, telecommunications, etc.

Internet of Things and BDS Application

Yuanyi Ma

Translating Tagore’s ‘Stray Birds’ into Chinese explores the choices in poetry translation in light of Systemic Functional Linguistics (SFL) and illustrates the ways in which readers can achieve a deeper understanding of translated works in English and Chinese. Focusing on Rabindranath Tagore’s ‘Stray Birds’, a collection of elegant and philosophical poems, as a source text, Ma and Wang analyse four Chinese target texts by Zheng Zhenduo, Yao Hua, Lu Jinde and Feng Tang and consider their linguistic complexities through SFL. This book analyses the source text and the target texts from the perspectives of the four strata of language, including graphology, phonology, lexicogrammar and context. Ideal for researchers and academics of SFL, Translation Studies, Linguistics, and Discourse Analysis, Translating Tagore’s ‘Stray Birds’ into Chinese provides an in-depth exploration of SFL and its emerging prominence in the field of Translation Studies.

Applying Systemic Functional Linguistics to Chinese Poetry Translation

Translating Tagore's Stray Birds into Chinese

M.A.K. Halliday (1925–2018) was the founder of Systemic Functional Linguistics (SFL) and, undoubtedly, one of the most influential linguists of his time, credited with changing the way that language and linguistics have been taught. SFL, as an appliable theory that approaches language as social semiotic, is the study of the relationship between language and its functions in social settings. Moreover, SFL conceives of language as a resource for making meaning and organizes language systemically as a huge network of interrelated choices of meaning. This book is an introduction to the life and seminal works of Halliday. Targeting both SFL and non-SFL scholars, this book introduces Halliday’s life and work in simple terms, expounds his theoretical conceptions, illustrates how his theories have been applied to various areas of linguistics and offers additional readings for researchers who want to explore this area further. Divided into six sections covering Hallidayan connections, theory and architecture of language, Hallidayan conceptions of language, systems and the modes of meaning, and applications of SFL, this accessible introduction is a key resource for researchers and students within the fields of linguistics and applied linguistics.

Introducing M.A.K. Halliday

Lao She’s Teahouse and Its Two English Translations: Exploring Chinese Drama Translation with Systemic Functional Linguistics provides an in-depth application of Systemic Functional Linguistics (SFL) to the study of Chinese drama translation, and theoretically explores the interface between SFL and drama translation. Investigating two English translations of the Chinese drama, Teahouse (茶馆 Cha Guan in Chinese) by Lao She, and translated by John Howard-Gibbon and Ying Ruocheng respectively, Bo Wang and Yuanyi Ma apply Systemic Functional Linguistics to point out the choices that translators have to make in translation. This book is of interest to graduates and researchers of Chinese translation and discourse studies.

Exploring Chinese Drama Translation with Systemic Functional Linguistics

Lao She's Teahouse and Its Two English Translations

Matt Stephens

Barry Boehm

Shobha Rani Dhalipathi

Doug Rosenberg

Charles Suscheck

From the beginning of software time, people have wondered why it isn’t possible to accelerate software projects by simply adding staff. This is sometimes known as the “nine women can’t make a baby in one month” problem. The most famous treatise declaring this to be impossible is Fred Brooks’ 1975 book The Mythical Man-Month, in which he declares that “adding more programmers to a late software project makes it later,” and indeed this has proven largely true over the decades. Aided by a domain-driven code generator that quickly creates database and API code, Parallel Agile (PA) achieves significant schedule compression using parallelism: as many developers as necessary can independently and concurrently develop the scenarios from initial prototype through production code. Projects can scale by elastic staffing, rather than by stretching schedules for larger development efforts. Schedule compression with a large team of developers working in parallel is analogous to hardware acceleration of compute problems using parallel CPUs. PA has some similarities with and differences from other Agile approaches. Like most Agile methods, PA "gets to code early" and uses feedback from executable software to drive requirements and design. PA uses technical prototyping as a risk-mitigation strategy, to help sanity-check requirements for feasibility, and to evaluate different technical architectures and technologies. Unlike many Agile methods, PA does not support "design by refactoring," and it doesn't drive designs from unit tests. Instead, PA uses a minimalist UML-based design approach (Agile/ICONIX) that starts out with a domain model to facilitate communication across the development team, and partitions the system along use case boundaries, which enables parallel development. Parallel Agile is fully compatible with the Incremental Commitment Spiral Model (ICSM), which involves concurrent effort of a systems engineering team, a development team, and a test team working alongside the developers. The authors have been researching and refining the PA process for several years on multiple test projects that have involved over 200 developers. The book’s example project details the design of one of these test projects, a crowdsourced traffic safety system.

Bo Wang

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