تحسين النتائح
ترتيب حسب
من
الى
الصفحة 12
الصفحة 12
Advances in Discrete Differential Geometry
On a newly emerging field of discrete differential geometry and an excellent way to access this exciting area. It surveys the fascinating connections between discrete models in differential geometry and complex analysis, integrable systems and applications in computer graphics. The authors take a closer look at discrete models in differential geometry and dynamical systems. Their curves are polygonal, surfaces are made from triangles and quadrilaterals, and time is discrete. Nevertheless, the difference between the corresponding smooth curves, surfaces and classical dynamical systems with continuous time can hardly be seen. This is the paradigm of structure-preserving discretizations. Current advances in this field are stimulated to a large extent by its relevance for computer graphics and mathematical physics.
Advances in Data Mining : Applications in E-Commerce, Medicine, and Knowledge Management
Presents papers describing selected projects on the topic of data mining in fields like e commerce, medicine, and knowledge management. The objective is to report on current results and at the same time to give a review on the present activities in this field in Germany. An effort has been made to include the latest scientific results, as well as lead the reader to the various fields of activity and the problems related to them. Knowledge discovery on the basis of web data is a wide and fast growing area. E commerce is the principal theme of motivation in this field, as companies invest large sums in the electronic market, in order to maximize their profits and minimize their risks. Other applications are telelearning, teleteaching, service support, and citizen information systems. Concerning these applications, there is a great need to understand and support the user by means of recommendation systems, adaptive information systems, as well as by personalization.
Advances in Biologically Inspired Information Systems : Models, Methods, and Tools
A comprehensive overview of the most promising research directions in the area of bio-inspired computing. According to the broad spectrum addressed by the different book chapters, a rich variety of biological principles and their application to ICT systems are presented.
Advances and applications of DSmT for information fusion: Collected works ; Vol.3
One of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule.
Advances and applications of DSmT for information fusion ; Vol. 4
One of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule.
Advancement of Deep Learning and its Applications in Object Detection and Recognition
In just the past five years, deep learning has taken the world by surprise, driving rapid progress in fields as diverse as computer vision, natural language processing, automatic speech recognition, etc. This book presents an introduction to deep learning and various applications of deep learning such as recommendation systems, text recognition, diabetic retinopathy prediction of breast cancer, prediction of epilepsy, sentiment, fake news detection, software defect prediction and protein function prediction.
Advanced sensors technologies applied in mobile robot
Contains contributions on the latest developments in mobile robotic systems and related research. Various topics with different ideas and applications from mobile robotics have found their place. New ideas are presented for mobile robots that specialise in cleaning floors, power lines and HVAC systems. We also find innovative approaches for navigation path planning using local minima-free potential fields, novel path primitives and/or their parameterisation for minimum-time planning, and various control approaches ranging from visual serving to model predictive and adaptive trajectory tracking, applied to wheeled robots, humanoid manipulators and flying robots. Localisation approaches using LiDAR, motion capture systems, fingerprint-based and biomechanical gait systems are also discussed.
Advanced engineering mathematics : A second course with MatLab
Presents a wide variety of topics needed by today's engineers. The fifth edition of that book, available now, has been broken into two parts: topics currently needed in mathematics courses and a new stand-alone volume presenting topics not often included in these courses and consequently unknown to engineering students and many professionals.
Advanced artificial intelligence models and its applications
The field of artificial intelligence (AI) has undergone enormous expansion since its inception in the mid-20th century, as demonstrated by its application across an array of engineering and scientific challenges. Particularly in the last decade, AI has witnessed a significant breakthrough with the advent of deep learning, which has facilitated the employment of various AI models across a multitude of domains. This reprint features ten papers accepted for publication in the Special Issue titled "Advanced Artificial Intelligence Models and Their Applications," published in the MDPI Mathematics journal. These papers explore numerous facets of advanced artificial intelligence models and their applications, covering areas such as cybersecurity, image classification, logistics optimization, automatic music generation, human capital investment, writer recognition, remote sensing image indexing, target tracking, and more.
Advanced Algorithms and Data Structures
introduces a collection of algorithms for complex programming challenges in data analysis, machine learning, and graph computing. You’ll discover cutting-edge approaches to a variety of tricky scenarios. You’ll even learn to design your own data structures for projects that require a custom solution. What's inside Build on basic data structures you already know Profile your algorithms to speed up application Store and query strings efficiently Distribute clustering algorithms with MapReduce Solve logistics problems using graphs and optimization algorithms
Advance Concepts of Image Processing and Pattern Recognition : Effective Solution for Global Challenges
Explains the important concepts and principles of image processing to implement the algorithms and techniques to discover new problems and applications. It contains numerous fundamental and advanced image processing algorithms and pattern recognition techniques to illustrate the framework. It presents essential background theory, shape methods, texture about new methods, and techniques for image processing and pattern recognition. It maintains a good balance between a mathematical background and practical implementation. This book also contains the comparison table and images that are used to show the results of enhanced techniques. This book consists of novel concepts and hybrid methods for providing effective solutions for society. It also includes a detailed explanation of algorithms in various programming languages like MATLAB, Python, etc.
Adaptive Motion of Animals and Machines
Apparently, the ability of animals and robots to adapt in a real world cannot be explained or realized by one single function in a control system and mechanism. That is, adaptation in motion is induced at every level from the central nervous system to the musculoskeletal system.Thus,weorganized the International Symposium on Adaptive Motion in Animals and Machines (AMAM) forscientist sandengineersconcerned with adaptation on various level stobebrought together todiscussprinciplesateachleveland to investigate principles governing total systems.
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
Adaptive agents and multi-agent systems II : Adaptation and multi-agent learning
Adaptive agents and multi-agent systems is an emerging and exciting interdisciplinary area of research and development involving artificial intelligence, software engineering, and developmental biology, as well as cognitive and social science. This book presents 17 revised and carefully reviewed papers taken from two workshops on the topic as well as 2 invited papers by leading researchers in the area. The papers deal with various aspects of machine learning, adaptation, and evolution in the context of agent systems and autonomous agents.
Abstract Computing Machines : A Lambda Calculus Perspective
The book addresses ways and means of organizing computations, highlighting the relationship between algorithms and the basic mechanisms and runtime structures necessary to execute them using machines. It completely abstracts from concrete programming languages and machine architectures, taking instead the lambda calculus as the basic programming and program execution model to design various abstract machines for its correct implementation. The emphasis is on fully normalizing machines based on full-fledged beta-reductions as essential prerequisites for symbolic computations that treat functions and variables truly as first-class objects. Their weakly normalizing counterparts are shown to be functional abstract machines that sacrifice the flavors of full beta-reductions for decidedly simpler runtime structures and improved runtime efficiency. Further downgrading of the lambda calculus leads to classical imperative machines that permit side-effecting operations on the runtime environment.
A Practical Theory of Reactive Systems : Incremental Modeling of Dynamic Behaviors
Presents a ""practical theory"" of reactive systems, with formal foundations in Temporal Logic of Actions. This book emphasises theoretical understanding of reactive behaviors and using ""horizontal"" modularity to manage their complexity. It illustrates the incremental specification by a number of examples of varying size and complexity
A Matrix Algebra Approach to Artificial Intelligence
The book consists of two parts: the first discusses the fundamentals of matrix algebra in detail, while the second focuses on the applications of matrix algebra approaches in AI. Highlighting matrix algebra in graph-based learning and embedding, network embedding, convolutional neural networks and Pareto optimization theory, and discussing recent topics and advances, the book offers a valuable resource for scientists, engineers, and graduate students in various disciplines
A first course in differential equations with modeling applications
A comprehensive treatment of ordinary differential equations, concisely presenting basic and essential results in a rigorous manner. Including various examples from physics, mechanics, natural sciences, engineering and automatic theory, Differential Equations is a bridge between the abstract theory of differential equations and applied systems theory.
3-D Shape Estimation and Image Restoration : Exploiting Defocus and Motion-Blur
Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene—as well as its radiance properties—and which in turn can be used to generate novel images with better quality. 3-D Shape Estimation and Image Restoration presents a coherent framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield "restored" images. It provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.
Master Dentistry ; Vol.1 : Oral and Maxillofacial Surgery, Radiology, Pathology and Oral Medicine
Provides a comprehensive overview of the oral and maxillofacial subjects in dentistry that students will need in order to pass their final exams. This invaluable adjunct to exam preparation provides a practical synthesis of core information, reflecting real-life case scenarios. Information is structured to enhance understanding and clinical decision making, and a variety of self-assessment methods prepare students for success. Comprehensively updated, the book covers a range of essential topics in the field of contemporary oral and maxillofacial subjects, including surgical flap design, state-of-the-art surgical techniques, zygomatic implants, molecular pathology, current imaging applications and pain management. The text is integrated and evidence based throughout. Covers oral and maxillofacial surgery, radiology, pathology and oral medicine subjects Brand new chapter on facial skin broadens diagnostic ability Range of self-assessment tasks to support learning Aligns to dental school curricula globally Concise and easy to follow Designed to support recall for examination purposes Practical guidance on examination preparation and skills Perfect for BDS exam preparation and candidates taking the MFDS, MJDF, ORE or other post-graduate exams
