Commentary On: Bauxite Mining Issue in Orissa. (Draft #1; I’ve just done my research and written up‚ i still have to put it all together‚ produce graphs and more) Article link : http://www.guardian.co.uk/business/2010/aug/24/vedanta-mine-plan-halted-indian-government In a conference or board meeting room‚ business leaders should get down to the nitty-gritty interest‚ such as minimizing social cost instead of minimizing private costs. Often long-term environmental damage is overlooked by short-term
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Watch PBS’s “FRONTLINE: Young & Restless in China” in 11 segments @ www.pbs.org/wbgh/pages/frontline/view ]. Report the things that are similar to the United States & those that are different‚ also comment on things that surprise you & that you find interesting. (20 points) “Young & Restless in China” shows many parallels between the types of social issues that are faced by the younger generations in both China and the United States. Both countries struggle with finding a balance
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China China Structural * Ah Xian’s ‘Bust 66’ in the series ‘China China’ is made from porcelain and overtop of closed mouth and eyes are the traditional Chinese landscape paintings of misty mountains‚ waterfalls and wooden bridges. * Ah Xian’s semi abstracted qualities of his work make the face look recessive and his use of shadows create a contemporary feel to the artwork. * This artwork evidently reflects his Chinese culture and heritage through the painted surface designs‚ yet
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Gains in China‚ India to boost Asia/Pacific demand China has shown strong growth in mining equipment demand‚ a direct result of investment in its local mining industry. For example‚ coal output nearly doubled from 2001 to 2006‚ reflecting the nation’s intense need for energy. China is also a major source of commodities such as iron ore and bauxite. Other major Asian markets for mining equipment include Australia and India. Like China‚ India has experienced a major growth in coal output. Australia
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------------------------------------------------- Tzu Han Hung (Vivian) CASE 2 1. Estimated profit by random selection Expected spending per catalog mailed = 0.053 * $103 = $5.46 Expected Gross Profit by random select= (5.46-2)*180‚000 = $622‚800 2. a) We applied partition to “All_data” sheet‚ and partition output is shown in “Data_Partition1” b) Logistic regression output can be seen in “LR_Output1”. Target variable is “purchase”. We select every variable except sequence_number(meaningless
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the business once the company develops connectedness and meaning‚ transforming it into information‚ knowledge‚ and eventually wisdom. As described in the case‚ the following are the benefits derived by the businesses: • Applebee’s utilized data mining technology to analyze both the front-of-house and back-of-house performances. They also used the stored data for effective inventory management (supplies replenishment) and identifying which products to promote. • Travelocity‚ an online travel site
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CHAPTER 6‚ Case #1 BETHESDA MINING To analyze this project‚ we must calculate the incremental cash flows generated by the project. Since net working capital is built up ahead of sales‚ the initial cash flow depends in part on this cash outflow. So‚ we will begin by calculating sales. Each year‚ the company will sell 500‚000 tons under contract‚ and the rest on the spot market. The total sales revenue is the price per ton under contract times 500‚000 tons‚ plus the spot market sales times the
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ALL THAT GLITTERS IS NOT GOLD The play‚ Death of a Salesman by Arthur Miller is a tragedy. It is about an American family who live their lives masking their reality‚ which is filled with tension and instability‚ with the American dream lifestyle. The father of the household‚ William Loman‚ is the driving force behind fantasizing these illusions. Hence‚ in the play‚ we are faced with many incidences where false perceptions occur and fall apart in the face of reality. We see evidence of this unmasked
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Recommended Systems using Collaborative Filtering and Classification Algorithms in Data Mining Dhwani Shah 2008A7PS097G Mentor – Mrs. Shubhangi Gawali BITSC331 2011 1 BITS – Pilani‚ K.K Birla Goa INDEX S. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. Topic Introduction to Recommended Systems Problem Statement Apriori Algorithm Pseudo Code Apriori algorithm Example Classification Classification Techniques k-NN algorithm Determine a good value of k References Page No. 3 5 5 7 14 16 19 24 26 2
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ALL THAT GLITTERS IS NOT GOLD Glasses breaking‚ voices shrieking‚ papers flying; Abigail huddled up in fear. ‘’You’ll die if you leave‚ don’t leave else you’ll die; be warned‚’’ these were the words reverberating in the ears of Abby; as her peers call her. ‘’Oh! Not again; not this time. Leave me alone. Please‚’’ she communicated to the voice through her thoughts but the voice kept on replying‚ ‘’Never‚ never. Your heart is here‚ you belong here.’’ Abigail’s mind was filled with reminiscences
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