| 綜合性 | |
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內容包含人文社會、文學小說、語言學習、財經商管、科學科普、電腦資訊、醫藥養生、藝術設計、休閒生活、考試證照各領域電子書，特別推薦語言學習有聲書。 |
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iRead eBooks 華藝電子書 airitiBooks 使用說明 內容包含商管財經、休閒旅遊、文學小說、語言學習，以及考試用書、教科書、學術專業圖書。 |
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以大學及專業出版社所出版的圖書為主，內容包含：研究型教科書、學術專著、美術及醫學等專題論述、中小學讀本等。語種多元，包含了繁簡中文、英文等語種出版品。 McGraw-Hill 專區 |
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與國內各出版社與作家合作的電子書，重新編排製作、互動設計，提供聯經、天下文化、大石國際文化(國家地理雜誌)、經濟日報、寶瓶文化、時報文化、讀書共和國等多家出版社的優質學術書籍。 |
| 電資領域 | |
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| 1 |
IGI InfoScience Computer Science & Information Technology User Guide IGI Global是專門出版電腦科學和資訊科技管理高品質研究的國際出版社，包含11個領域、350多個主題，為最新、最即時的研究。 |
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IOS Press為成立於1990年的STM(Scientific、Technical and Medical )國際專業出版社，主題包含計算機科學、數學、醫學和自然科學；全文以PDF直接閱讀，提供主題、書名瀏覽及檢索功能。 |
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為iGroup開發的線上電子書平台，與超過100家世界知名出版機構合作、出版其數位內容。本校購買以下工科領域出版社之電子書： Momentum Press Society for Industrial and Applied Mathematics (SIAM) |
| 4 |
World Scientific世界科技出版社為重要的科學主題出版社，許多出版的書籍為世界知名大學史丹佛、東大、劍橋、麻省理工等使用教科書，其作者編輯網羅諾貝爾獎得主與各領域知名專業學者。 |
| 綜合性 | |
|---|---|
| 1 |
Cambridge Core (原Cambridge Books Online (CBO) 電子書) 收錄劍橋大學出版社之電子書，主題相當廣泛，包含醫學類、人文類、社會科學類、自然科學類等。 |
| 2 |
eBooks on EBSCOhost (原名:NetLibrary電子書) User Guide 為英文綜合學科之電子書，可直接線上閱讀、或下載至載具離線閱讀 (支援多載具)。 |
| 3 |
Elsevier eBooks on ScienceDirect 為Elsevier出版社經營的電子資源平台，涵蓋生化、遺傳學和分子生物學、化學、臨床醫學、工程學和獸醫學等學科。 |
| 4 |
ProQuest Ebook Central MyiLibrary電子書 User Guide MyiLibrary於2018年併為ProQuest Ebook Central平台，涵蓋綜合類十大主題，提供多種欄位檢索及主題瀏覽，提供線上閱讀及整本或特定章節下載。 |
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SpringerLink 施普林格電子書 館藏查詢 全球最大的學術出版社，提供Springer出版社之電子書與電子叢書。 |
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Taylor & Francis 電子書 Computer Science 收錄Taylor & Francis、Routledge、Psychology Press、CRC Press等多家出版社的學術專業參考書。 |
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為國際知名專業出版機構John Wiley & Sons所出版之電子書平台，內容涵蓋商業、化學、電腦科學、地球與環境科學、教育、工程、法律、生命科學、數學與統計、醫學與公共衛生、物理與天文、聚合物與材料科學、心理學等領域。 |
Advanced Deep Learning Applications in Big Data Analytics by
Interest in big data has swelled within the scholarly community as has increased attention to the internet of things (IoT). Algorithms are constructed in order to parse and analyze all this data to facilitate the exchange of information. However, big data has suffered from problems in connectivity, scalability, and privacy since its birth. The application of deep learning algorithms has helped process those challenges and remains a major issue in today's digital world. Advanced Deep Learning Applications in Big Data Analytics is a pivotal reference source that aims to develop new architecture and applications of deep learning algorithms in big data and the IoT. Highlighting a wide range of topics such as artificial intelligence, cloud computing, and neural networks, this book is ideally designed for engineers, data analysts, data scientists, IT specialists, programmers, marketers, entrepreneurs, researchers, academicians, and students.
Exploiting Semantic Web Knowledge Graphs in Data Mining by
Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process.This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation strategies from types and relations in knowledge graphs used in different data mining tasks such as classification, regression, and outlier detection. Part II, Semantic Web Knowledge Graphs Embeddings, proposes an approach that circumvents the shortcomings introduced with the approaches in Part I, developing an approach that is able to embed complete Semantic Web knowledge graphs in a low dimensional feature space where each entity and relation in the knowledge graph is represented as a numerical vector. Finally, Part III, Applications of Semantic Web Knowledge Graphs, describes a list of applications that exploit Semantic Web knowledge graphs like classification and regression, showing that the approaches developed in Part I and Part II can be used in applications in various domains.The book will be of interest to all those working in the field of data mining and KDD.
Smartphone-Based Real-Time Digital Signal Processing by
Real-time or applied digital signal processing courses are offered as follow-ups to conventional or theory-oriented digital signal processing courses in many engineering programs for the purpose of teaching students the technical know-how for putting signal processing algorithms or theory into practical use. These courses normally involve access to a teaching laboratory that is equipped with hardware boards, in particular DSP boards, together with their supporting software. A number of textbooks have been written discussing how to achieve real-time implementation on these hardware boards. This book discusses how to use smartphones as hardware boards for real-time implementation of signal processing algorithms, thus providing an alternative to the hardware boards that are used in signal processing laboratory courses. The fact that mobile devices, in particular smartphones, have become powerful processing platforms led to the development of this book to enable students to use their own smartphones to run signal processing algorithms in real-time considering that these days nearly all students possess smartphones. Changing the hardware platforms that are currently used in applied or real-time signal processing courses to smartphones creates a truly flexible laboratory experience or environment for students. In addition, it relieves the cost burden associated with using dedicated signal processing boards noting that the software development tools for smartphones are free of charge and are well-maintained by smartphone manufacturers. This book is written in such a way that it can be used as a textbook for real-time or applied digital signal processing courses offered at many universities. Ten lab experiments that are commonly encountered in such courses are covered in the book. It is written primarily for those who are already familiar with signal processing concepts and are interested in their real-time and practical aspects. Similar to existing real-time courses, knowledge of C programming is assumed. This book can also be used as a self-study guide for those who wish to become familiar with signal processing app development on either Android or iOS smartphones/tablets.
Marine Big Data by
As the volume of marine big data has increased dramatically, one of the main concerns is how to fully exploit the value of such data in the development of marine economy and marine science and technology.The book covers data acquisition, feature classification, processing and applications of marine big data in evaluation and decision-making, using case studies such as storm surge and marine oil spill disaster.
