In any sketch of the Wampanoag Tribe of Indians, Massasoit, and his renowned son, Pometacom, or King Philip, must of necessity be the central figures. The first, as the early friend and sturdy ally and preserver of the Plymouth settlement in its years of feebleness, and the latter as the bold and intrepid leader of his race, in their wild and desperate effort to stay the march of civilization, and reclaim the hunting grounds of their fathers from the adventurous intruders who had entered in and possessed the land.The first knowledge we have of the Indians in this section, is from Verrazzano, a Florentine pilot, who was sent out by Francis I, of France, in 1524, in command of the ship Dolphin, or Dauphin. He sailed from Madeira on the 17th of January, 1524, with fifty men and eight months stores, and steering west, in fifty days made land; which proved to be what is now a portion of the Carolina coast.
The Paper I read last winter before the Royal Geographical Society on our explorations in the Selkirks being necessarily limited as to detail, I thought it might prove interesting to some to have a fuller account. I have therefore in the following pages attempted, while describing our wanderings and scrambles, to give as complete a picture as possible of the most striking phenomena of the region we visited. Our map, now reproduced, was published in the Proceedings of the Royal Geographical Society for March, 1889, and it has been to me no small gratification to receive letters from travellers in Canada, the United States, and at home, men not previously known to me, saying that they found it useful, and that it helped them to enjoy the scenery of the Selkirks during the past summer.Though all the time at our disposal was devoted to rendering our map as accurate as possible, more careful surveys will find many corrections necessary in detail.
My native place is the city of Padua: I am of a Roman family, which had resided there for many years. The state and trou bles of Italy in 1800, which are too well known to require any comment from me.
It is of course impossible to go up and down feet without some climbing, in the popular sense of that word. But in the technical Alpine sense we had far too little mountaineering for my taste. Rope and ice-axe played but a very subordinate part in our journey. This was our mis fortune rather than our fault. The tremendous rainstorm of September 1899, after devastating Darjiling and its tea-gardens, swept across Kangchenjunga into Tibet in the form of a premature snowfall, lowering the snow-level nearly 4000 feet and practically closing the highest region.
It was not until many years later that careful investigation in several distinct localities revealed the true succession of the rocks and the distribution among them Of the fossils (graptolites) which they contain. These investigations first made it possible to trace in detail various rock — groups, and to map the chief axes Of folding and the more important displacements or faults which affect the strata.
The conferences on `applications for computers and operations research in the minerals industry' (apcom) initially focused on the optimization of geostatistics and resource estimation. Several standard methods used in these fields were presented in the early days of apcom. While geostatistics remains an important part, information technology has emerged, and nowadays apcom not only focuses on geostatistics and resource estimation, but has broadened its horizon to information and communication technology (ict) in the mineral industry. Mining goes digital is a collection of 90 high quality, peer reviewed papers covering recent ict-related developments in: - geostatistics and resource estimation- mine planning- scheduling and dispatch - mine safety and mine operation- internet of things, robotics- emerging technologies - synergies from other industries - general aspects of digital transformation in mining mining goes digital will be of interest to professionals and academics involved or interested in the above-mentioned areas.
The Business of Mining complete set of three Focus books will provide readers with a holistic all-embracing appraisal of the analytical tools available for assessing the economic viability of prospective mines. Each volume has a discrete focus. This second volume discusses, in some depth, alternative means of assessing the economic viability of mining projects based on the best estimate of the recoverable mineral and/or fossil fuel reserves. The books were written primarily for undergraduate applied geologists, mining engineers and extractive metallurgists and those pursuing course-based postgraduate programs in mineral economics. However, the complete series will also be an extremely useful reference text for practicing mining professionals as well as for consultant geologists, mining engineers or primary metallurgists.
The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.
This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.
A hands-on guide to making valuable decisions from data using advanced data mining methods and techniques This second installment in the Making Sense of Data series continues to explore a diverse range of commonly used approaches to making and communicating decisions from data. Delving into more technical topics, this book equips readers with advanced data mining methods that are needed to successfully translate raw data into smart decisions across various fields of research including business, engineering, finance, and the social sciences. Following a comprehensive introduction that details how to define a problem, perform an analysis, and deploy the results, Making Sense of Data II addresses the following key techniques for advanced data analysis: Data Visualization reviews principles and methods for understanding and communicating data through the use of visualization including single variables, the relationship between two or more variables, groupings in data, and dynamic approaches to interacting with data through graphical user interfaces. Clustering outlines common approaches to clustering data sets and provides detailed explanations of methods for determining the distance between observations and procedures for clustering observations. Agglomerative hierarchical clustering, partitioned-based clustering, and fuzzy clustering are also discussed. Predictive Analytics presents a discussion on how to build and assess models, along with a series of predictive analytics that can be used in a variety of situations including principal component analysis, multiple linear regression, discriminate analysis, logistic regression, and Naïve Bayes. Applications demonstrates the current uses of data mining across a wide range of industries and features case studies that illustrate the related applications in real-world scenarios.
- 1
- 2
- 3
- 4
- 5
- 6
- 13
隐私声明 | 电子书 | 出版社
主办单位:中国教育图书进出口有限公司
京ICP备11007853号-12 
京公网安备 11010802027623号
Copyright ©爱学术平台 2021, All Rights Reserved