The Nest of Students

Ruwan Rajapakse ... 508 pages - Publisher: Butterworth-Heinemann; 2nd edition (December, 2015) ... Language: English - ISBN-10: 0128046988 - ISBN-13: 978-0128046982. 

Geotechnical Engineering Calculations and Rules of Thumb, Second Edition, offers geotechnical, civil and structural engineers a concise, easy-to-understand approach to selecting the right formula and solving even most difficult calculations in geotechnical engineering. A "quick look up guide", this book places formulas and calculations at the reader’s finger tips. In this book, theories are explained in a "nutshell" and then the calculation is presented and solved in an illustrated, step-by-step fashion. In its first part, the book covers the fundamentals of Geotechnical Engineering: Soil investigation, condition and theoretical concepts. In the second part it addresses Shallow Foundations, including bearing capacity, elastic settlement, foundation reinforcement, grillage design, footings, geogrids, tie and grade beams, and drainage. This session ends with a chapter on selecting foundation types. The next part covers Earth Retaining Structures and contains chapters on its basic concepts and types, gabion walls and reinforced earth walls. The following part covers Geotechnical Engineering Strategies providing coverage of softwares, instrumentation, excavations, raft design, rock mechanics, dip angle and strike, rock stabilization equipment, soil anchors, tunnel design, seismology, geosynthetics, and slurry cutoff walls. The final part is on Pile Foundations including content on design on sandy soils, clay soils, pin piles, negative skin friction, caissons and pile clusters. In this new and updated edition the author has incorporated new software calculation tools, current techniques for foundation design, liquefaction information, seismic studies, laboratory soil tests, geophysical techniques, new concepts for foundation design and Dam designs. All calculations have been updated to most current material characteristics available in the market. Practicing Geotechnical, Civil and Structural Engineers may find in this book an excellent companion to their day-to day work, benefiting from the clear and direct calculations, examples, and cases. Civil Engineering students may find particular interest in the concise theory presented in the beginning of each chapter. Calculations both in FPS and SI metric systems; Convenient access to all needed calculations; Access to concise theory that helps understand the calculations; Case studies from around the world; Includes new software calculation tools.

The first introductory geotechnical engineering textbook to cover both saturated and unsaturated soil mechanics: Most books designed for an introductory course in geotechnical engineering focus on saturated soil mechanics. Geotechnical Engineering: Unsaturated and Saturated Soils takes a new approach, based on the fundamentals of unsaturated soils and extends the description to a wide variety of applications.

Written by an international leader in the field, this comprehensive introduction presents geotechnical engineering as dealing with a true three-phase soil while treating saturated soil as a special case, rather than the other way around. It covers numerous topics that reveal the vast domain covered by geotechnical engineering and its important contributions to many elements of infrastructure. It includes, in addition to conventional subjects, a number of topics typically left out of undergraduate geotechnical courses, such as: Engineering geology + Rocks + Site investigation and in situ tests + Geophysics + Problem solving methods and soil models + Thermodynamics for soils + Earthquake geo-engineering + Erosion + Geoenvironmental + Geosynthetics + Ground improvement+ Technical communications. Geotechnical Engineering: Unsaturated and Saturated Soils takes students beyond the usual confines of an undergraduate introduction to become a useful reference as they enter graduate studies or begin their careers.

Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need + Quickly review all the Python you need to start building machine learning applications + Master the AI and ML tool chain and project lifecycle + Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn + Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems + Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services + Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more + Work with Microsoft Azure AI APIs + Walk through building six real-world AI applications, from start to finish.

This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories:

The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10.

The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.

Jasbir Singh Arora ... 912 pages - Publisher: Academic Press; 4th edition (April, 2016) - Language: English - ISBN-10: 0128008067 - ISBN-13: 978-0128008065.

Introduction to Optimum Design, Fourth Edition, carries on the tradition of the most widely used textbook in engineering optimization and optimum design courses. It is intended for use in a first course on engineering design and optimization at the undergraduate or graduate level in engineering departments of all disciplines, with a primary focus on mechanical, aerospace, and civil engineering courses. Through a basic and organized approach, the text describes engineering design optimization in a rigorous, yet simplified manner, illustrates various concepts and procedures with simple examples, and demonstrates their applicability to engineering design problems.

Formulation of a design problem as an optimization problem is emphasized and illustrated throughout the text using Excel and MATLAB as learning and teaching aids. This fourth edition has been reorganized, rewritten in parts, and enhanced with new material, making the book even more appealing to instructors regardless of course level. Includes basic concepts of optimality conditions and numerical methods that are described with simple and practical examples, making the material highly teachable and learnable + Presents applications of optimization methods for structural, mechanical, aerospace, and industrial engineering problems + Provides practical design examples that introduce students to the use of optimization methods early in the book + Contains chapter on several advanced optimum design topics that serve the needs of instructors who teach more advanced courses.