The Nest of Students

Jianye Ching ... 188 pages - Language: ‎English - Publisher: CRC Press; (August, 2024).

Bayesian data analysis and modelling linked with machine learning offers a new tool for handling geotechnical data. This book presents recent advancements made by the author in the area of probabilistic geotechnical site characterization.

Two types of correlation play central roles in geotechnical site characterization: cross-correlation among soil properties and spatial-correlation in the underground space. The book starts with the introduction of Bayesian notion of probability “degree of belief”, showing that well-known probability axioms can be obtained by Boolean logic and the definition of plausibility function without the use of the notion “relative frequency”. It then reviews probability theories and useful probability models for cross-correlation and spatial correlation. Methods for Bayesian parameter estimation and prediction are also presented, and the use of these methods demonstrated with geotechnical site characterization examples.

Plaxis 2D and 3D 2024 (v24.02.00.1144) (Size: 4.0 GB) ... The PLAXIS development team is pleased to announce the availability of PLAXIS 2D and 3D 2024. Perform advanced finite element or limit equilibrium analysis of soil and rock deformation and stability, as well as soil structure interaction, groundwater, and heat flow.

The latest releases of PLAXIS marks our definitive transition to becoming part of Seequent, The Bentley Subsurface Company, with some minor cosmetic changes and a change to the version numbering. Benefit from workflow enhancements for rock and mining engineers, a new material model and SoilTest options for users working with unsaturated soils. PLAXIS 2D enters the world of subsurface digital twins and PLAXIS Monopile Designer users can improve their designs with additional design criteria. PLAXIS 2D is a powerful and user friendly finite element package intended for two-dimensional analysis of deformation and stability in geotechnical engineering and rock mechanics. PLAXIS is used worldwide by top engineering companies and institutions in the civil and geotechnical engineering industry. Applications range from excavations, embankment and foundations to tunnelling, mining and reservoir geomechanics. PLAXIS is equipped with a broad range of advanced features to model a diverse range of geotechnical problems, all from within a single integrated software package. PLAXIS uses predefined structural elements and loading types in a CAD-like environment. This empowers the user with fast and efficient model creation, allowing more time to interpret the results.

Plaxis 3D is a software for analyzing the finite element stability and soil transformation in geotechnical engineering. The program, with its many features, fully analyzes geotechnical structures from different angles, and this analysis is based on the scientific and theoretical foundations that the researchers of this scientific branch have achieved. Plaxis 3D Foundation defines complex structures consisting of artificial structures and soil in separation modes, and separate work is possible on each mode. This user-friendly product is designed to be highly flexible in modeling and simulation, has a powerful processing core, and performs post-processing processes well. With its various features, this program is one of the best in the field of geotechnical engineering. plaxis is a company that specializes in geotechnical software and in addition to software, conferences and research seminars around the world. The banking software is based on a finite element analysis method that is used effectively in two-dimensional and three-dimensional products. The seminars held by Plexiglas are not about the software software training, but about the transfer of engineering knowledge among the members. Both to improve the quality of their products and to transfer the technical knowledge and achievements of the day among the researchers in this field.

Brij B. Gupta, Mamta ... 369 pages - Language: ‎English - Publisher: ‎World Scientific Publishing Company; (December, 2023).

With the proliferation of information, big data management and analysis have become an indispensable part of any system to handle such amounts of data. The amount of data generated by the multitude of interconnected devices increases exponentially, making the storage and processing of these data a real challenge.

Big data management and analytics have gained momentum in almost every industry, ranging from finance or healthcare. Big data can reveal key insights if handled and analyzed properly; it has great application potential to improve the working of any industry. This book covers the spectrum aspects of big data; from the preliminary level to specific case studies. It will help readers gain knowledge of the big data landscape.

Highlights of the topics covered include description of the Big Data ecosystem; real-world instances of big data issues; how the Vs of Big Data (volume, velocity, variety, veracity, valence, and value) affect data collection, monitoring, storage, analysis, and reporting; structural process to get value out of Big Data and recognize the differences between a standard database management system and a big data management system.

Readers will gain insights into choice of data models, data extraction, data integration to solve large data problems, data modelling using machine learning techniques, Spark's scalable machine learning techniques, modeling a big data problem into a graph database and performing scalable analytical operations over the graph and different tools and techniques for processing big data and its applications including in healthcare and finance.

Jeffrey Paul Wheeler ... 474 pages - Language: English - Publisher: ‎Chapman and Hall/CRC; (December, 2023).

The primary goal of this text is a practical one. Equipping students with enough knowledge and creating an independent research platform, the author strives to prepare students for professional careers. Providing students with a marketable skill set requires topics from many areas of optimization. The initial goal of this text is to develop a marketable skill set for mathematics majors as well as for students of engineering, computer science, economics, statistics, and business. Optimization reaches into many different fields.

This text provides a balance where one is needed. Mathematics optimization books are often too heavy on theory without enough applications; texts aimed at business students are often strong on applications, but weak on math. The book represents an attempt at overcoming this imbalance for all students taking such a course.

The book contains many practical applications but also explains the mathematics behind the techniques, including stating definitions and proving theorems. Optimization techniques are at the heart of the first spam filters, are used in self-driving cars, play a great role in machine learning, and can be used in such places as determining a batting order in a Major League Baseball game. Additionally, optimization has seemingly limitless other applications in business and industry. In short, knowledge of this subject offers an individual both a very marketable skill set for a wealth of jobs as well as useful tools for research in many academic disciplines.

Many of the problems rely on using a computer. Microsoft’s Excel is most often used, as this is common in business, but Python and other languages are considered. The consideration of other programming languages permits experienced mathematics and engineering students to use MATLAB® or Mathematica, and the computer science students to write their own programs in Java or Python.

Tanvir Mustafy, T. Ur Rahman ... 281 pages - Language: ‎English - Publisher: ‎Springer; (January, 2024).

This textbook summarizes the different statistical, scientific, and financial data analysis methods for users ranging from a high school level to a professional level. It aims to combine the data analysis methods using three different programs—Microsoft Excel, SPSS, and MATLAB. The book combining the different data analysis tools is a unique approach. The book presents a variety of real-life problems in data analysis and machine learning, delivering the best solution. Analysis methods presented in this book include but are not limited to, performing various algebraic and trigonometric operations, regression modeling, and correlation, as well as plotting graphs and charts to represent the results. Fundamental concepts of applied statistics are also explained here, with illustrative examples. Thus, this book presents a pioneering solution to help a wide range of students, researchers, and professionals learn data processing, interpret different findings derived from the analyses,and apply them to their research or professional fields.