الصفحة 6
الصفحة 6
Deep learning architecture and application
As one of the fastest-growing topics in machine learning, deep learning algorithms have achieved unprecedented success in recent years. Novel paradigms (such as contrastive learning and few-shot learning) in deep learning and rising neural network architectures (e.g., transformer and masked autoencoder) are dramatically changing the field of data-driven algorithms. More importantly, deep learning models are redefining the next generation of industrial applications spanning image recognition, speech processing, language translation, healthcare, and other sciences. For example, recent advances in deep representation learning are allowing us to learn about protein 3D structures, which sheds new light on fundamental medicine and biology along with potentially bringing in billions of dollars (e.g., in the pharmaceutical market).
Deep learning and computer vision in remote sensing-II
Computer vision (CV) have seen a massive rise in popularity in the remote sensing field over the last few years. This success is mostly due to the effectiveness of deep learning (DL) algorithms. However, remote sensing data acquisition and annotation, as well as information extraction from massive remote sensing data, are still challenging. This reprint collected novel developments in the field of deep learning and computer vision methods for remote sensing. Papers dealing with fundamental theoretical analyses, as well as those demonstrating their application to real-world problems, have been published. With practical examples and real-world case studies, this reprint provides a valuable resource for researchers, professionals, and students seeking to harness the power of deep learning in the field of remote sensing.
Deep learning and computer vision in remote sensing-I
In the last few years, huge amounts of progress have been made regarding remote sensing in the field of computer vision. This success and progress is mostly due to the effectiveness of deep learning (DL) algorithms. In addition, the remote sensing community has shifted its attention to DL, and DL algorithms have been used to achieve significant success in many image analysis tasks. However, with regard to remote sensing, a number of challenges caused by difficulties in data acquisition and annotation have not been fully solved yet. This reprint is a collection of novel developments in the field of remote sensing using computer vision, deep learning, and artificial intelligence. The articles published involve fundamental theoretical analyses as well as those demonstrating their application to real-world problems.
Database theory - ICDT 2005 ; 10th international conference, Edinburgh, UK, January 5-7, 2005, Proceedings
This volume collects the papers presented at the 10th International Conference on Database Theory, ICDT 2005, held during January 5–7, 2005, in Edinburgh, UK. ICDT (http://alpha.luc.ac.be/~lucp1080/icdt/) has now a long tra- tion of international conferences, providing a biennial scienti?c forum for the communication of high-quality and innovative research results on theoretical - pects of all forms of database systems and database technology. The conference usually takes place in Europe, and has been held in Rome (1986), Bruges (1988), Paris (1990), Berlin (1992), Prague (1995), Delphi (1997), Jerusalem (1999), London (2001), and Siena (2003) so far. ICDT has merged with the Sym- sium on Mathematical Fundamentals of Database Systems (MFDBS), initiated in Dresden in 1987, and continued in Visegrad in 1989 and Rostock in 1991. ICDT had a two-stage submission process. First, 103 abstracts were subm- ted, which were followed a week later by 84 paper submissions. From these 84 submissions, the ICDT Program Committee selected 24 papers for presentation at the conference. Most of these papers were “extended abstracts” and preli- nary reports on work in progress. It is anticipated that most of these papers will appear in a more polished form in scienti?c journals.
Database System Concepts
Presents the fundamental concepts of database management. This text is suitable for a first course in databases at the junior/senior undergraduate level or the first year graduate level
Data science in theory and practice : Techniques for big data analytics and complex data sets
Delivers a comprehensive treatment of the mathematical and statistical models useful for analyzing data sets arising in various disciplines, like banking, finance, health care, bioinformatics, security, education, and social services. Written in five parts, the book examines some of the most commonly used and fundamental mathematical and statistical concepts that form the basis of data science. The authors go on to analyze various data transformation techniques useful for extracting information from raw data, long memory behavior, and predictive modeling. Readers will also learn from topics like: Analyses of foundational theoretical subjects, including the history of data science, matrix algebra and random vectors, and multivariate analysis A comprehensive examination of time series forecasting, including the different components of time series and transformations to achieve stationarity Introductions to both the R and Python programming languages, including basic data types and sample manipulations for both languages An exploration of algorithms, including how to write one and how to perform an asymptotic analysis A comprehensive discussion of several techniques for analyzing and predicting complex data sets
Data Integration in the Life Sciences ; Vol. 4075 ; 3rd International Workshop, DILS 2006, Hinxton, UK, July 20-22, 2006, Proceedings
Data management and data integration are fundamental problems in the life sciences. Advances in molecular biology and molecular medicine are almost u- versallyunderpinned by enormouse?orts in data management,data integration, automatic data quality assurance, and computational data analysis. Many hot topics in the life sciences, such as systems biology, personalized medicine, and pharmacogenomics, critically depend on integrating data sets and applications producedby di?erent experimentalmethods, in di?erent researchgroups,andat di?erent levels of granularity.
Data communications and network technologies
Aims to help readers master the basics of network communications and use Huawei network devices to set up enterprise LANs and WANs, wired networks, and wireless networks, ensure network security for enterprises, and grasp cutting-edge computer network technologies. The content of this book includes: network communication fundamentals, TCP/IP protocol, Huawei VRP operating system, IP addresses and subnetting, static and dynamic routing, Ethernet networking technology, ACL and AAA, network address translation, DHCP server, WLAN, IPv6, WAN PPP and PPPoE protocol, typical networking architecture and design cases of campus networks, SNMP protocol used by network management, operation and maintenance, network time protocol NTP, SND and NFV, programming, and automation.
Data Center Handbook : Plan, Design, Build, and Operations of a Smart Data Center ; 2nd ed.
Explains the fundamentals, advanced technologies, and best practices used in planning, designing, building and operating a mission-critical, energy-efficient, sustainable data center. This handbook, in its second edition, covers anatomy, ecosystem and taxonomy of data centers that enable the Internet of Things and artificial intelligent ecosystems and encompass the following: Data center overview and strategic planning Data center technologies Data center design and construction Data center operations technologies
Data and Computer Communications
It is ideal for one/two-semester courses in Computer Networks, Data Communications, and Communications Networks in CS, CIS, and Electrical Engineering departments. This book is also suitable for Product Development personnel, Programmers, Systems Engineers, Network Designers and others involved in the design of data communications and networking products. With a focus on the most current technology and a convenient modular format, this best-selling text offers a clear and comprehensive survey of the entire data and computer communications field. Emphasizing both the fundamental principles as well as the critical role of performance in driving protocol and network design, it explores in detail all the critical technical areas in data communications, wide-area networking, local area networking, and protocol design.
Cyber-physical systems of systems : Foundations : A conceptual model and some derivations : The AMADEOS legacy
Technical Systems-of-Systems (SoS) – in the form of networked, independent constituent computing systems temporarily collaborating to achieve a well-defined objective – form the backbone of most of today’s infrastructure. The energy grid, most transportation systems, the global banking industry, the water-supply system, the military equipment, many embedded systems, and a great number more, strongly depend on systems-of-systems. The correct operation and continuous availability of these underlying systems-of-systems are fundamental for the functioning of our modern society.
CSS Mastery : Advanced Web Standards Solutions
This book is your indispensable guide to cutting-edge CSS development—all you need to work your way up to CSS professional. While CSS is a relatively simple technology to learn, it is a difficult one to master. When you first start developing sites using CSS, you will come across all kinds of infuriating browser bugs and inconsistencies. It sometimes feels like there are a million and one different techniques to master, spread across a bewildering array of websites. The range of possibilities seems endless and makes for a steep and daunting learning curve. It begins with a brief recap of CSS fundamentals such as the importance of meaningful markup, how to structure and maintain your code, and how the CSS layout model really works.
Cost-Based Oracle Fundamentals
In Cost-Based Oracle Fundamentals, the first book in a series of three, Jonathan Lewis—one of the foremost authorities in this field—describes the most commonly used parts of the model, what the optimizer does with your statistics, and why things go wrong. With this information, you'll be in a position to fix entire problem areas, not just single SQL statements, by adjusting the model or creating more truthful statistics.
Core Java ; Vol. I : Fundamentals ; 12th ed.
The definitive guide to writing robust, maintainable code. Whatever version of Java you are using—up to and including Java 17—this book will help you achieve a deep and practical understanding of the language and APIs. With hundreds of realistic examples, Cay S. Horstmann reveals the most powerful and effective ways to get the job done.
Conceptual Modeling - ER 2007 ; 26th International Conference on Conceptual Modeling, Auckland, New Zealand, November 5-9, 2007, Proceedings
Conceptual modeling is fundamental to the development of complex systems, because it provides the key communication means between systems developers, end-users and customers.Conceptua lmodeling provides languages,methods and tools to understand and represent the application domain;to elicitate,concepalize and formalize system requirements and user needs;to communicate systems designs to all stakeholders; to formally verify and validate system designs on high levels of abstractions; and to minimize ambiguities in system development. Initially, conceptual modeling mainly addressed data-intensive information s- tems and contributed to data modeling and database application engineering. The area of conceptual modeling has now matured to encompass all kinds of application areas such as e-applications (including e-business and e-learning), web-based systems (including the semantic web and ubiquitous systems), life science and geographic applications.
Conceptual Modeling - ER 2005
Conceptual modeling is fundamental to any domain where one must cope with complex real-world situations and systems because it fosters communication - tween technology experts and those who would bene?t from the application of those technologies. Conceptual modeling is the key mechanism for und- standing and representing the domains of information system and database - gineering but also increasingly for other domains including the new “virtual” e-environmentsandtheinformationsystemsthatsupportthem.Theimportance of conceptual modeling in software engineering is evidenced by recent interest in “model-drivenarchitecture”and“extremenon-programming”.Conceptualm- eling also plays a prominent rolein various technical disciplines and in the social sciences. The Annual International Conference on Conceptual Modeling (referred to as the ER Conference) provides a central forum for presenting and discussing current research and applications in which conceptual modeling is the major emphasis.
Computer vision : Algorithms and applications
Explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos. Suitable for an upper-level undergraduate or graduate-level course in computer science or engineering, this textbook focuses on basic techniques that work under real-world conditions and encourages students to push their creative boundaries. Its design and exposition also make it eminently suitable as a unique reference to the fundamental techniques and current research literature in computer vision.
Computer Viruses : from theory to applications
The purpose of this book is to propose a teaching approach to under- 1 stand what computer viruses really are and how they work. To do this, three aspects are covered ranging from theoretical fundamentals, to pr- tical applications and technical features; fully detailed, commented source 1 We will systematically use the plural form “viruses” instead of the litteral one “virii”. The latter is now an obsolete, though gramatically recommended, form. VIII Preface codes of viruses as well as inherent applications are proposed. So far, the applications-oriented aspects have hardly ever been addressed through the scarce existing literature devoted to computer viruses.
Computer Security in the 21st Century
Computer Security in the 21st Century shares some of the emerging important research trends reflected in recent advances in computer security, including: security protocol design, secure peer-to-peer and ad hoc networks, multimedia security, and intrusion detection, defense and measurement. Highlights include presentations of : * Fundamental new security * Cryptographic protocols and design, * A new way of measuring network vulnerability: attack surfaces, * Network vulnerability and building impenetrable systems, * Multimedia content protection including a new standard for photographic images, JPEG2000. Researchers and computer security developers will find in this book interesting and useful insights into building computer systems that protect against computer worms, computer viruses, and other related concerns.
Computer science : Theory and applications ; 15th International computer science symposium in Russia, CSR 2020, Yekaterinburg, Russia, June 29 – July 3, 2020, Proceedings
This book constitutes the proceedings of the 15th International Computer Science Symposium in Russia, CSR 2020, held in Yekaterinburg, Russia, in June 2020. The 25 full papers and 6 invited papers were carefully reviewed and selected from 49 submissions. The papers cover a broad range of topics, such as: algorithms and data structures; computational complexity, including hardness of approximation and parameterized complexity; randomness in computing, approximation algorithms, fixed-parameter algorithms; combinatorial optimization, constraint satisfaction, operations research; computational geometry; string algorithms; formal languages and automata, including applications to computational linguistics; codes and cryptography; combinatorics in computer science; computational biology; applications of logic to computer science, proof complexity; database theory; distributed computing; fundamentals of machine learning, including learning theory, grammatical inference and neural computing; computational social choice; quantum computing and quantum cryptography; theoretical aspects of big data.
