6th period 3 May 2012 Polar Pioneers Thirteen months into an Antarctic exploration Roald Amundsen found him and his fellow explorers engulfed by a sea of eternal ice. There was no escaping the lingering death traps surrounding the ship‚ without waiting for the frozen sea to release them. So they waited‚ for thirteen months‚ hunting seals and making warm clothes out of blankets (“Roald Amundsen”). This is one of many stories of Artic pioneers who have endured the treacherous components the
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Project Topic 1: What is the Impact of Mining on South Africa and its people? GOLD Authors: Michelle Dandara‚ Kirsten Collins‚ Robyn Blench‚ Yumna Badrooien and Sonia Mataramvura Date of Completion: 17 February 2012 Teacher: Mr Altern Abstract Mining plays a very important role in South Africa: it is one of the driving forces behind South Africa’s booming economy and provides employment for millions of South Africans. South Africa boasts world-scale primary mining processing facilities and is a world
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Data Mining On Medical Domain Smita Malik‚ Karishma Naik‚ Archa Ghodge‚ Shivani Gaunker Shree Rayeshwar Institute of Engineering & Information Technology Shiroda‚ Goa‚ India. Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com Abstract-The successful application of data mining in highly visible fields like retail‚ marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries
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Data Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus‚ data mining should have been more appropriately named “knowledge mining from data‚” which is unfortunately somewhat long. Knowledge mining‚ a shorter term‚ may not
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fluxicon Process Mining Tutorial Copyright © 2013 Fluxicon fluxicon Goals of this tutorial • Understand phases of process mining analysis • Be able to get started and play around with your own data fluxicon Outline 1. Example Scenario 2. Roadmap 3. Hands-on Session 4. Take-away Points fluxicon Example Scenario Purchasing process ERP Requester Requester Manager Purchasing Agent Supplier Financial Manager fluxicon Problems 1. Inefficient
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Mining in the Philippines Concerns and conflicts Report of a Fact-Finding Trip to the Philippines July-August 2006 Acknowledgments The Fact Finding Mission wishes to thank all those who took time to meet with us. The right to enjoy human rights and development is universal. We wish to encourage any and all communities and local authorities adversely affected by mining impacts to continue to explore and pursue all avenues available within the law at local‚ national and international levels
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governing the minerals industry in the Philippines is contained in Republic Act No. 7942 (otherwise known as the Philippine Mining Act of 1995) and given flesh by its revised implementing rules and regulations (Administrative Order No. 96-40) and its subsequent amendments. These policies advocate the sustainable development of mineral resources in the country. While both the Mining Act and its regulations provide a strong focus on environmental and social management‚ they continue to be the subject
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MANAGEMENT INFORMATION SYSTEM CASE STUDY: WHITMANN PRICE CONSULTANT SUBMITTED BY: SUBMITTED TO: Manish Dhungel Sandip Timsina MBAe Spring 2013 Lecturer Sec: ‘A’ MIS 1. What different types of needs can MISs and DSSs fulfill in Whitmann
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Data is related in many ways Develop the larger picture Multi-dimensional view of data DSS Database Requirements Data Extraction and Filtering End User Analytical Interface Must support advanced data modeling and data presentation tools Data analysis tools Query generation Must Allow the User to Navigate through the DSS Size Requirements VERY Large – Terabytes Advanced Hardware (Multiple processors‚ multiple disk arrays‚ etc.) Data Warehouse Definition: Integrated‚ Subject-Oriented‚ Time-Variant
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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