Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, the actual modern machines used in surface mining are equipped with diagnostic systems that automatically trace all important machine parameters and send this information to the main producer’s computer. Such data not only provide information on the technical properties of the machine but they also have a statistical character. Furthermore, all information gathered during stand and lab investigations where parts, assemblies and whole devices are tested in order to prove their usefulness, have a stochastic character. All of these materials need to be developed statistically and, more importantly, based on these results mining engineers must make decisions whether to undertake actions, connected with the further operation of the machines, the further development of the works, etc. For these reasons, knowledge of modern statistics is necessary for mining engineers; not only as to how statistical analysis of data should be conducted and statistical synthesis should be done, but also as to understanding the results obtained and how to use them to make appropriate decisions in relation to the mining operation. This book on statistical analysis and synthesis starts with a short repetition of probability theory and also includes a special section on statistical prediction. The text is illustrated with many examples taken from mining practice; moreover the tables required to conduct statistical inference are included.
Written by a mineral engineer for mineral engineers, and packed with real world examples, this book de-mystifies the statistics that most of us learned at university and then forgot. It shows how simple statistical methods, most of them available in Excel, can be used to make good decisions in the face of experimental uncertainty. Written in accessible language, it explains how experimental uncertainty arises from the normal measurement errors and how statistics provides a powerful methodology to manage that uncertainty. It assumes only that the readers are numerate, can use Excel, and want to do a better professional job. It is aimed squarely at mineral engineers and allied professionals (such as chemists) on the mine site, in head office, in engineering and supply companies and in universities. Most of the examples are illustrated in Excel but Minitab is also used for advanced techniques. The book includes over 100 Excel and Minitab hints. Example spreadsheets can be downloaded from the JKMRC and JKTech websites.
Recent rough estimates are that the U.S. Department of Defense (DoD) spends at least $38 billion a year on the research, development, testing, and evaluation of new defense systems; approximately 40 percent of that cost-at least $16 billion-is spent on software development and testing. There is widespread understanding within DoD that the effectiveness of software-intensive defense systems is often hampered by low-quality software as well as increased costs and late delivery of software components. Given the costs involved, even relatively incremental improvements to the software development process for defense systems could represent a large savings in funds. And given the importance of producing defense software that will carry out its intended function, relatively small improvements to the quality of defense software systems would be extremely important to identify. DoD software engineers and test and evaluation officials may not be fully aware of a range of available techniques, because of both the recent development of these techniques and their origination from an orientation somewhat removed from software engineering, i.e., from a statistical perspective. The panel's charge therefore was to convene a workshop to identify statistical software engineering techniques that could have applicability to DoD systems in development.
Vol.1 : Données de Base - Vol. 2 : Consommation d'énergie
Publisher: OECD Publishing
PREVIOUSLY PUBLISHED AS INDUSTRIAL STRUCTURE STATISTICS, VOLUME 1: Core Data, VOLUME 2: Energy Consumption In this seventeenth edition, Volume 1, Core Data, provides official annual data for detailed industrial sectors (mining and quarrying ...
Publisher: Society for Mining, Metallurgy, and Exploration
Category: Technology & Engineering
Modern American Coal Mining: Methods and Applications covers a full range of coal mining and coal industry topics, with chapters written by leading coal mining industry professionals and academicians. Highlights from the book include coal resources and distribution, mine design, advances in strata control and power systems, improvements in surface mining, ventilation to reduce fires and explosions, drilling and blasting, staffing requirement ratios, management and preplanning, and coal preparation and reclamation. The text is enhanced with 11 case studies that are representative of underground and surface mines in the United States. Narrative descriptions and appropriate mine plans are presented, with attention given to unique features and situations that are addressed through mine design and construction. A useful glossary is included, as are many examples, figures, equations and tables, to make the text even more useful.
Over the last few decades, there are increasing public awareness of adverse events involving engineering failures that not only led to monetary losses but also more importantly, human injuries and deaths. Whilst it is vital for an engineering professional or student to acquire the necessary technical knowledge and skills in their respective field, they must also understand the ethical essences that are relevant to their profession. Engineering professionals like biomedical engineers, need to appreciate the fundamentals of best practices and recognise how any derivation from such practices can have undesirable impacts on human lives. Through this book, it is hoped that readers would draw the relevance between the study of ethics and biomedical engineering. The book would be a useful source and reference for college-level and university-level students. Moreover, the contents are written so as to also provide valuable insights even for existing biomedical engineers and those enrolled in continual engineering education programs.
Advances in technology are making massive data sets common in many scientific disciplines, such as astronomy, medical imaging, bio-informatics, combinatorial chemistry, remote sensing, and physics. To find useful information in these data sets, scientists and engineers are turning to data mining techniques. This book is a collection of papers based on the first two in a series of workshops on mining scientific datasets. It illustrates the diversity of problems and application areas that can benefit from data mining, as well as the issues and challenges that differentiate scientific data mining from its commercial counterpart. While the focus of the book is on mining scientific data, the work is of broader interest as many of the techniques can be applied equally well to data arising in business and web applications. Audience: This work would be an excellent text for students and researchers who are familiar with the basic principles of data mining and want to learn more about the application of data mining to their problem in science or engineering.