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The Advanced CSS Collection
by Craig Buckler Ilya Bodrov-Krukowski Claudio Ribeiro Tiffany B Brown David Attard Ahmed Bouchefra Giulio Mainardi Diego SouzaCSS has grown from a language for formatting documents into a robust language for designing web applications. Its syntax is easy to learn, making CSS a great entry point for those new to programming. Indeed, it's often the second language that developers learn, right behind HTML. As CSS's feature set and abilities have grown, so has its depth. In this collection of books, we'll be exploring some of the amazing things that developers can do with CSS today; tasks that in the past might only have been achievable with some pretty complex JavaScript, if at all. This collection contains: Modern CSS, which explores topics like variable fonts and transforms, and shows how they might be used in the real worldCSS Grid Layout: 5 Practical Projects, which shows five complete projects that utilize the Grid Layout Layout moduleCSS Tools & Skills which looks at essential CSS tools and skills for modern front-end developers
Advanced Cybersecurity Technologies
by Ralph MoseleyCybersecurity is an extremely important area which is rapidly evolving, necessarily, to meet current and future threats. Anyone who studies within this domain requires a particular skillset and way of thinking, balancing technical knowledge and human insight. It is vital to recognize both sides of this complex area and integrate the two. This book looks at the technical fields progressively, building up in layers before expanding into more advanced topics. Each area is looked at succinctly, describing the main elements and problems in each area and reinforcing these concepts with practical coding examples, questions and ideas for further research. The book builds on an overview of basic architecture of systems and networks, setting a context for how information is vulnerable. Cryptography is explained in detail with examples, showing the steady progress in this area over time through to the possibilities of quantum encryption. Steganography is also explained, showing how this can be used in a modern-day context through multimedia and even Virtual Reality. A large section of the book is given to the technical side of hacking, how such attacks occur, how they can be avoided and what to do after there has been an intrusion of some description. Cyber countermeasures are explored, along with automated systems of defense, whether created by the programmer or through firewalls and suchlike. The human aspect of cyber security is detailed along with the psychology and motivations for launching attacks. Social engineering is focused on and with the various techniques looked at – revealing how an informed individual, organization or workplace can protect themselves against incursions and breaches. Finally, there is a look the latest developments in the field, and how systems, such as the IoT are being protected. The book is intended for advanced undergraduate and postgraduate courses on cybersecurity but is also useful for those studying IT or Computer Science more generally.
Advanced Data Acquisition and Intelligent Data Processing (River Publishers Series In Information Science And Technology Ser.)
by Vladimír Haasz Kurosh MadaniDAQ and data processing is a basic part of all automated production systems, diagnostic systems, watching over quality of production, energy distribution, transport control or in various other areas. Demands on the speed, accuracy and reliability increase in general. It is possible to achieve not only using superior (but also more expensive) hardware, but also applying advanced data acquisition and intelligent data processing. It deals e.g. optimal data fusion of a number of sensors, new stochastic methods for accuracy increasing, new algorithms for acceleration of data processing, etc. These are the grounds for publishing this book. Advanced Data Acquisition and Intelligent Data Processing offers 10 up-to-date examples of different applications of advanced data acquisition and intelligent data processing used in monitoring, measuring and diagnostics systems. The book arose based on the most interesting papers from this area published at IDAACS?2013 conference. However, the indivudual chapters include not only designed solution in wider context but also relevant theoretical parts, achieved results and possible future ways.Technical topics discussed in this book include: • advanced methods of data acquisition in application that are not routine;• measured data fusion using up-to-date advanced data processing;• nonlinear dynamical systems identification;• multidimensional image processing.Advanced Data Acquisition and Intelligent Data Processing is ideal for personnel of firms deals with advanced instrumentation, energy consumption monitoring, environment monitoring, non-descructive diagnostics robotics, etc., as well as academic staff and postgraduate students in electrical, control and computer engineering.Content: 1. Introduction; 2. Waveform acquisition with resolutions exceeding those of the ADC employed; 3. Different Disaggregation Algorithms in Non-Intrusive Home Energy Monitoring Systems; 4. Design and testing of an electronic nose system sensitive to the aroma of truffles; 5. DAQ System for Ultrasonic Transducer Evaluation under Spread Spectrum Excitation; 6. Optimal Data Fusion in Decentralized Stochastic Unknown Input Observers; 7. Odor Classification by Neural Networks; 8. ANFIS Based Approach for Improved Multisensors Signal Processing; 9. Neuro-Fuzzy Sensor's Linearization Based FPGA; 10. Interpolation Method of Nonlinear Dynamical Systems Identification Based on Volterra Model in Frequency Domain ; 11. Training Cellular Automata for Hyperspectral Image Segmentation
Advanced Data Analytics Using Python: With Machine Learning, Deep Learning and NLP Examples
by Sayan MukhopadhyayGain a broad foundation of advanced data analytics concepts and discover the recent revolution in databases such as Neo4j, Elasticsearch, and MongoDB. This book discusses how to implement ETL techniques including topical crawling, which is applied in domains such as high-frequency algorithmic trading and goal-oriented dialog systems. You’ll also see examples of machine learning concepts such as semi-supervised learning, deep learning, and NLP. Advanced Data Analytics Using Python also covers important traditional data analysis techniques such as time series and principal component analysis. <p><p> After reading this book you will have experience of every technical aspect of an analytics project. You’ll get to know the concepts using Python code, giving you samples to use in your own projects.
Advanced Data Analytics Using Python: With Architectural Patterns, Text and Image Classification, and Optimization Techniques
by Sayan Mukhopadhyay Pratip SamantaUnderstand advanced data analytics concepts such as time series and principal component analysis with ETL, supervised learning, and PySpark using Python. This book covers architectural patterns in data analytics, text and image classification, optimization techniques, natural language processing, and computer vision in the cloud environment.Generic design patterns in Python programming is clearly explained, emphasizing architectural practices such as hot potato anti-patterns. You'll review recent advances in databases such as Neo4j, Elasticsearch, and MongoDB. You'll then study feature engineering in images and texts with implementing business logic and see how to build machine learning and deep learning models using transfer learning. Advanced Analytics with Python, 2nd edition features a chapter on clustering with a neural network, regularization techniques, and algorithmic design patterns in data analytics with reinforcement learning. Finally, the recommender system in PySpark explains how to optimize models for a specific application. What You'll LearnBuild intelligent systems for enterpriseReview time series analysis, classifications, regression, and clusteringExplore supervised learning, unsupervised learning, reinforcement learning, and transfer learning Use cloud platforms like GCP and AWS in data analyticsUnderstand Covers design patterns in Python Who This Book Is ForData scientists and software developers interested in the field of data analytics.
Advanced Data Communications and Networks
by Bill BuchananThe use of data communications and computer networks is constantly increasing, bringing benefits to most of the countries and peoples of the world, and serving as the lifeline of industry. Now there is a textbook that discusses data communications and networking in a readable form that can be easily understood by students who will become the IS professionals of the future.Advanced Data Communications and Networks provides a comprehensive and practical treatment of rapidly evolving areas. The text is divided into seven main sections and appendices:"General data compression"Video, images, and sound"Error coding and encryption"TCP/IP and the Internet"Network operating systems"LANs/WANs"Cables and connectorsOther topics include error detection/correction, image/video compression, digital video, digital audio, TCP/IP, HTTP, electronic mail, HTML, Windows NT, NetWare, UNIX, Fast Ethernet, ATM, FDDI, and much more.Written by a respected academician who is also an accomplished engineer, this textbook uses the author's wide practical experience in applying techniques and theory toward solving real engineering problems. It also includes an accompanying Web site that contains software, source code, and other supplemental information.
Advanced Data Mining and Applications: 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, November 28–30, 2022, Proceedings, Part II (Lecture Notes in Computer Science #13726)
by Weitong Chen Lina Yao Taotao Cai Shirui Pan Tao Shen Xue LiThe two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.
Advanced Data Mining and Applications: 18th International Conference, ADMA 2022, Brisbane, QLD, Australia, November 28–30, 2022, Proceedings, Part I (Lecture Notes in Computer Science #13725)
by Weitong Chen Lina Yao Taotao Cai Shirui Pan Tao Shen Xue LiThe two-volume set LNAI 13725 and 13726 constitutes the proceedings of the 18th International Conference on Advanced Data Mining and Applications, ADMA 2022, which took place in Brisbane, Queensland, Australia, in November 2022. The 72 papers presented in the proceedings were carefully reviewed and selected from 198 submissions. The contributions were organized in topical sections as follows: Finance and Healthcare; Web and IoT Applications; On-device Application; Other Applications; Pattern Mining; Graph Mining; Text Mining; Image, Multimedia and Time Series Data Mining; Classification, Clustering and Recommendation; Multi-objective, Optimization, Augmentation, and Database; and Others.
Advanced Data Mining and Applications: 14th International Conference, ADMA 2018, Nanjing, China, November 16–18, 2018, Proceedings (Lecture Notes in Computer Science #11323)
by Guojun Gan Bohan Li Xue Li Shuliang WangThis book constitutes the refereed proceedings of the 14th International Conference on Advanced Data Mining and Applications, ADMA 2018, held in Nanjing, China in November 2018. The 23 full and 22 short papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers were organized in topical sections named: Data Mining Foundations; Big Data; Text and Multimedia Mining; Miscellaneous Topics.
Advanced Data Mining and Applications: 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings (Lecture Notes in Computer Science #10604)
by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li and Aixin SunThis book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos.
Advanced Data Mining and Applications: 12th International Conference, ADMA 2016, Gold Coast, QLD, Australia, December 12-15, 2016, Proceedings (Lecture Notes in Computer Science #10086)
by Jinyan Li, Xue Li, Shuliang Wang, Jianxin Li and Quan Z. ShengThis book constitutes the proceedings of the 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, held in Gold Coast, Australia, in December 2016. The 70 papers presented in this volume were carefully reviewed and selected from 105 submissions. The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.
Advanced Data Mining and Applications: 17th International Conference, ADMA 2021, Sydney, NSW, Australia, February 2–4, 2022, Proceedings, Part II (Lecture Notes in Computer Science #13088)
by Bohan Li Lin Yue Jing Jiang Weitong Chen Xue Li Guodong Long Fei Fang Han YuThis book constitutes the proceedings of the 17th International Conference on Advanced Data Mining and Applications, ADMA 2021, held in Sydney, Australia in February 2022.*The 26 full papers presented together with 35 short papers were carefully reviewed and selected from 116 submissions. The papers were organized in topical sections in Part II named: Pattern mining; Graph mining; Text mining; Multimedia and time series data mining; and Classification, clustering and recommendation. * The conference was originally planned for December 2021, but was postponed to 2022.
Advanced Data Mining and Applications: 17th International Conference, ADMA 2021, Sydney, NSW, Australia, February 2–4, 2022, Proceedings, Part I (Lecture Notes in Computer Science #13087)
by Bohan Li Lin Yue Jing Jiang Weitong Chen Xue Li Guodong Long Fei Fang Han YuThis book constitutes the proceedings of the 17th International Conference on Advanced Data Mining and Applications, ADMA 2021, held in Sydney, Australia in February 2022.*The 26 full papers presented together with 35 short papers were carefully reviewed and selected from 116 submissions. The papers were organized in topical sections in Part I, including: Healthcare, Education, Web Application and On-device application. * The conference was originally planned for December 2021, but was postponed to 2022.
Advanced Data Mining and Applications: 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part V (Lecture Notes in Computer Science #15391)
by Quan Z. Sheng Gill Dobbie Jing Jiang Xuyun Zhang Wei Emma Zhang Yannis Manolopoulos Jia Wu Wathiq Mansoor Congbo MaThis six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
Advanced Data Mining and Applications: 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part III (Lecture Notes in Computer Science #15389)
by Quan Z. Sheng Gill Dobbie Jing Jiang Xuyun Zhang Wei Emma Zhang Yannis Manolopoulos Jia Wu Wathiq Mansoor Congbo MaThis six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
Advanced Data Mining and Applications: 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part VI (Lecture Notes in Computer Science #15392)
by Quan Z. Sheng Gill Dobbie Jing Jiang Xuyun Zhang Wei Emma Zhang Yannis Manolopoulos Jia Wu Wathiq Mansoor Congbo MaThis six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
Advanced Data Mining and Applications: 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part II (Lecture Notes in Computer Science #15388)
by Quan Z. Sheng Gill Dobbie Jing Jiang Xuyun Zhang Wei Emma Zhang Yannis Manolopoulos Jia Wu Wathiq Mansoor Congbo MaThis six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
Advanced Data Mining and Applications: 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part IV (Lecture Notes in Computer Science #15390)
by Quan Z. Sheng Gill Dobbie Jing Jiang Xuyun Zhang Wei Emma Zhang Yannis Manolopoulos Jia Wu Wathiq Mansoor Congbo MaThis six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
Advanced Data Mining and Applications: 20th International Conference, ADMA 2024, Sydney, NSW, Australia, December 3–5, 2024, Proceedings, Part I (Lecture Notes in Computer Science #15387)
by Quan Z. Sheng Gill Dobbie Jing Jiang Xuyun Zhang Wei Emma Zhang Yannis Manolopoulos Jia Wu Wathiq Mansoor Congbo MaThis six-volume set, LNAI 15387-15392, constitutes the refereed proceedings of the 20th International Conference on Advanced Data Mining and Applications, ADMA 2024, held in Sydney, New South Wales, Australia, during December 3–5, 2024. The 159 full papers presented here were carefully reviewed and selected from 422 submissions. These papers have been organized under the following topical sections across the different volumes: - Part I : Applications; Data mining. Part II : Data mining foundations and algorithms; Federated learning; Knowledge graph. Part III : Graph mining; Spatial data mining. Part IV : Health informatics. Part V : Multi-modal; Natural language processing. Part VI : Recommendation systems; Security and privacy issues.
Advanced Data Mining and Applications: 15th International Conference, ADMA 2019, Dalian, China, November 21–23, 2019, Proceedings (Lecture Notes in Computer Science #11888)
by Shuliang Wang Xue Li Jianxin Li Sen Wang Shaowen QinThis book constitutes the proceedings of the 15th International Conference on Advanced Data Mining and Applications, ADMA 2019, held in Dalian, China in November 2019. The 39 full papers presented together with 26 short papers and 2 demo papers were carefully reviewed and selected from 170 submissions. The papers were organized in topical sections named: Data Mining Foundations; Classification and Clustering Methods; Recommender Systems; Social Network and Social Media; Behavior Modeling and User Profiling; Text and Multimedia Mining; Spatial-Temporal Data; Medical and Healthcare Data/Decision Analytics; and Other Applications.
Advanced Data Mining and Applications: 19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part V (Lecture Notes in Computer Science #14180)
by Xiaochun Yang Heru Suhartanto Guoren Wang Bin Wang Jing Jiang Bing Li Huaijie Zhu Ningning CuiThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
Advanced Data Mining and Applications: 19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part IV (Lecture Notes in Computer Science #14179)
by Xiaochun Yang Heru Suhartanto Guoren Wang Bin Wang Jing Jiang Bing Li Huaijie Zhu Ningning CuiThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
Advanced Data Mining and Applications: 19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part III (Lecture Notes in Computer Science #14178)
by Xiaochun Yang Heru Suhartanto Guoren Wang Bin Wang Jing Jiang Bing Li Huaijie Zhu Ningning CuiThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
Advanced Data Mining and Applications: 19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part II (Lecture Notes in Computer Science #14177)
by Xiaochun Yang Heru Suhartanto Guoren Wang Bin Wang Jing Jiang Bing Li Huaijie Zhu Ningning CuiThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.
Advanced Data Mining and Applications: 19th International Conference, ADMA 2023, Shenyang, China, August 21–23, 2023, Proceedings, Part I (Lecture Notes in Computer Science #14176)
by Xiaochun Yang Heru Suhartanto Guoren Wang Bin Wang Jing Jiang Bing Li Huaijie Zhu Ningning CuiThis book constitutes the refereed proceedings of the 19th International Conference on Advanced Data Mining and Applications, ADMA 2023, held in Shenyang, China, during August 21–23, 2023.The 216 full papers included in this book were carefully reviewed and selected from 503 submissions. They were organized in topical sections as follows: Data mining foundations, Grand challenges of data mining, Parallel and distributed data mining algorithms, Mining on data streams, Graph mining and Spatial data mining.