Macro diet for dummies
Teaches you everything you need to know to master the popular meal plan that has helped athletes, celebrities, and people just like you build lean muscle and lose fat for good. On the macro diet, you track macronutrients instead of calories, so you know you’re giving your body the correct balance of daily nutrients to feel energized, strong, and healthy. And the great thing is that, as long as you balance your macros and meet your daily goals, you can eat whatever you want. You'll reach your weight and health goals without feeling deprived of your favorite foods.
Machine Learning Refined : Foundations, Algorithms, and Applications
Provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology.
Machine learning refined : Foundations, algorithms, and applications
Providing a unique approach to machine learning, this text contains fresh and intuitive, yet rigorous, descriptions of all fundamental concepts necessary to conduct research, build products, tinker, and play. By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization
Machine Learning for Audio, Image and Video Analysis : Theory and Applications
The book is organized in four parts: The first focuses on technical aspects, basic mathematical notions and elementary machine learning techniques. The second provides an extensive survey of most relevant machine learning techniques for media processing, while the third part focuses on applications and shows how techniques are applied in actual problems. The fourth part contains detailed appendices that provide notions about the main mathematical instruments used throughout the text
Machine Learning Approaches in Cyber Security Analytics
Introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.
Machine learning approach for cloud data analytics in IoT
Covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications. Elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Machine Learning and Knowledge Discovery in Databases ; European Conference, ECML PKDD 2008, Antwerp, Belgium, September 15-19, 2008, Proceedings, Part I
Constitutes the refereed proceedings of the joint conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2008, held in Antwerp, Belgium, in September 2008.The 100 papers presented in two volumes, together with 5 invited talks, were carefully reviewed and selected from 521 submissions. In addition to the regular papers the volume contains 14 abstracts of papers appearing in full version in the Machine Learning Journal and the Knowledge Discovery and Databases Journal of Springer.
Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks
Communication and network technology has witnessed recent rapid development and numerous information services and applications have been developed globally. These technologies have high impact on society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication. Machine learning and cognitive computing have converged to give some groundbreaking solutions for smart machines. With these two technologies coming together, the machines can acquire the ability to reason similar to the human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.
Macchine matematiche : Dalla storia alla scuola = Mathematical Machines: From History to School
Presents the main mathematical machines for drawing curves, for applying geometrical transformations or for making classical perspectives.The publication constitutes an example of how history of mathematics may be useful for teaching today’s mathematics.
Low Thermal Expansion Glass Ceramics
Describes the fundamental principles, the manufacturing process, and applications of low thermal expansion glass ceramics. The composition, structure, and stability of polycrystalline materials having a low thermal expansion are described, and it is shown how low thermal expansion glass ceramics can be manufactured from appropriately chosen glass compositions. Examples illustrate the formation of this type of glass ceramic by utilizing normal production processes together with controlled crystallization. Thus glass ceramics with thermal coefficients of expansion of less than 0.3 x 10(-6)K(-1) can be obtained. Even for the mass production of high-quality cooktop panels (Ceran®., oven windows, and other household appliances a high reproducibility of the properties is achieved. Special glass ceramics (Zerodur®. for technological and scientific applications such as high-precision optics or large astronomical mirrors are likewise discussed. The completely revised edition also features new sections on glass-ceramic applications, with details on their performance, CDC-grinding, and laser gyroscopes containing Zerodur®..
Low Molecular Mass Gelators : Design, Self-Assembly, Function
Chapter 1 presents the physical principles of the growth mechanism of fiber and fiber network with LMGs, as treated on the basis of the heterogeneous nucleation model. in Chaps. 2 and 3, respectively. These chapters are intended to outline useful synthetic guidelines for the generation of an ever-increasing variety of molecular architectures within these two families of gelators. Recent developments in the chemistry of nucleobase-containing LMGs are described in Chap. 4. Hydrogen-bonding within these molecular systems involves complementary base pair formation, a process relevant to DNA double-helix formation The self-assembly of chiral organo- or hydrogelators is the subject of Chap. 5. result from the orthogonal self-assembly of liquid crystals and LMGs are presented in Chap. 6. The volume concludes with Chap. 7, a review of the emerging field of dendritic gels.
Loss and Damage from Climate Change : Concepts, Methods and Policy Options
Provides an authoritative insight on the Loss and Damage discourse by highlighting state-of-the-art research and policy linked to this discourse and articulating its multiple concepts, principles and methods. Written by leading researchers and practitioners, it identifies practical and evidence-based policy options to inform the discourse and climate negotiations. With climate-related risks on the rise and impacts being felt around the globe has come the recognition that climate mitigation and adaptation may not be enough to manage the effects from anthropogenic climate change.
Long-Term Ecosystem Changes in Riparian Forests
Presents and analyzes the results of more than 30 years of long-term ecological research in riparian forest ecosystems with the aim of casting light on changes in the dynamics of riparian forests over time.
Longs COVID-19 patients
Nearly 250 million people around the world have recovered from Covid-19. But here, the word "recovered" refers only to the acute phase of the illness. Approximately 10 and 40 percent of Covid patients continue to experience symptoms several weeks to months after falling sick, a nebulous condition now referred to as post-Covid condition, or long Covid. In long Covid, we are witnessing the emergence of a legitimate new illness, officially recognized by the World Health Organization's International Classification of Diseases...
Logics in Artificial Intelligence ; 11th European Conference, JELIA 2008, Dresden, Germany, September 28-October 1, 2008. Proceedings
Constitutes the refereed proceedings of the 11th European Conference on Logics in Artificial Intelligence, JELIA 2008, held in Dresden, Germany, Liverpool, in September/October 2008.The 32 revised full papers presented together with 2 invited talks were carefully reviewed and selected from 98 submissions. The papers cover a broad range of topics including belief revision, description logics, non-monotonic reasoning, multi-agent systems, probabilistic logic, and temporal logic.
Logging in Java with the JDK 1.4 Logging API and Apache log4j
In development scenarios where things can't be run in a debugger, or when you run the risk of masking the problem, logs are the greatest source of information about running a program. Pro Apache Log4j, Second Edition provides best practices guidelines and comprehensive coverage of the most recent release. Step by step, the book explains core concepts, from basic to advanced. Code samples are in Java and include guidelines for different application-specific needs. You'll also learn how to extend the API to write custom components and best practices for using the feature-rich log4j API. This book concludes with enterprise Java applications using log4j with JSP and J2EE.
Location- and Context-Awareness ; Vol. 3987 ; 2nd International Workshop, LoCA 2006, Dublin, Ireland, May 10-11, 2006, Proceedings
Contain the papers presented at the 2 International Workshop on Location- and Context-Awareness in May of 2006. As computing moves increasingly into the everyday world, the importance of location and context knowledge grows. The range of contexts encountered while sitting at a desk working on a computer is very limited compared to the large variety of situations experienced away from the desktop. For computing to be relevant and useful in these situations, the computers must have knowledge of the user’s activity, resources, state of mind, and goals, i.e., the user’s context, of which location is an important indicator. This workshop was intended to present research aimed at sensing, inferring, and using location and context data in ways that help the user.
Location- and Context-Awareness ; Vol. 3479 ; First International Workshop, LoCA 2005, Oberpfaffenhofen, Germany, May 12-13, 2005, Proceedings
The workshop was organized by the Institute of Communications and Navigation of the German Aerospace Center (DLR) in Oberpfa?enhofen, and the Mobile and Distributed Systems Group of the University of Munich. During the workshop, novel positioning algorithms and location sensing techniques were discussed, comprising not only enhancements of singular systems, like positioning in GSM or WLAN, but also hybrid technologies, such as the integration of global satellite systems with inertial positioning. Furthermore, improvements in sensor technology, as well as the integration and fusion of sensors, were addressed both on a theoretical and on an implementation level. Personal and confidential data, such as location data of users, have p- found implications for personal information privacy. Thus privacy protection, privacy-oriented location-aware systems, and how privacy aspects the feasibility and usefulness of systems were also addressed in the workshop.
Location- and context-awareness ; 3rd International Symposium, LoCA 2007, Oberpfaffenhofen, Germany, September 20-21, 2007, Proceedings
These proceedings contain the papers presented at the 3rd International S- posium on Location- and Context-Awareness in September of 2007. Computing has become mobile, wireless, and portable. The rangeof contexts encountered while sitting at a desk working on a computer is very limited c- pared to the large variety of situations experienced away from the desktop.
Local Pattern Detection ; International Seminar Dagstuhl Castle, Germany, April 12-16, 2004, Revised Selected Papers
Introduction The dramatic increase in available computer storage capacity over the last 10 years has led to the creation of very large databases of scienti?c and commercial information. The need to analyze these masses of data has led to the evolution of the new field knowledge discovery in databases (KDD) at the intersection of machine learning, statistics and database technology. Being interdisciplinary by nature, the field offers the opportunity to combine the expertise of different fields into a common objective. Moreover, within each field diverse methods have been developed and justified with respect to different quality criteria. We have to investigate how these methods can contributet o solving the problem of KDD. Traditionally, KDD was seeking to end global models for the data that - plain most of the instances of the database and describe the general structure of the data. Examples are statistical time series models, cluster models, logic programs with high coverageor classi?cation models like decision trees or linear decision functions. In practice, though, the use of these models often is very l- ited, because global models tend to end only the obvious patterns in the data, 1 which domain experts already are aware of . What is really of interest to the users are the local patterns that deviate from the already-known background knowledge. David Hand, who organized a workshop in 2002, proposed the new field of local patterns.



















