PPT-Strategies for Uncertain Times

Polyester R D Udeshi Reliance Industries Limited Contents 2 Changing Global Economics Fending Volatile Prices Protecting Profitability Supply Adequacy Sourcing Reliably Global Growth Rising Concerns New Avenues. Australias Foreign and Trade Policy White Paper A Commentary and Critique Should Australia Have an East Asian Doctrine brPage 20br An Awkward Partner Britain in the European Community Australian Journal of International Affairs The Japanese Journal 55 21 1260 1000 6 X 18 1155 18 1080 857 6 X 14 1155 14 840 667 6 X 105 halfpage horizontal 1155 105 630 500 6 X 7 1155 7 420 333 6 X 525 1155 525 315 250 5 X 21 96 21 1050 833 5 X 1575 96 1575 7875 625 5 X 14 96 14 700 556 5 X 105 96 105 525 417 5 X Volume. Temperature. Mass. Reading the Meniscus. Always read volume from the bottom of the . meniscus. . The meniscus is the curved surface of a liquid in a narrow cylindrical container.. Try to avoid parallax errors.. Doug Burdick, Prasad Deshpande, T. S. . Jayram. , . Raghu . Ramakrishnan. , . Shivakumar. . Vaithyanathan. Presented by . Raghav. . Sagar. OLAP Overview. Online Analytical Processing (OLAP). Interactive analysis of data, allowing data to be summarized and viewed in different ways in an online . Roger Levy. UC San Diego. LSA Institute 2011. 26 . July 2011. Garden Paths: What we don’t understand so well. In previous days we covered “ideal-observer” models of syntactic comprehension. Today we’ll add nuance to this picture. School of Computing. National University of Singapore. Department of Computer Science. Aalborg. University. Meihui. Zhang. , Su Chen, Christian S. Jensen, . Beng. Chin . Ooi. , . Zhenjie. Zhang. Data Uncertainty: . Modeling and Querying. Mohamed F. Mokbel. Department of Computer Science and Engineering. University of Minnesota. www.cs.umn.edu/~mokbel. mokbel@cs.umn.edu. 2. Talk Outline. Introduction to Uncertain Data. Chapter 1: An Overview of Probabilistic Data Management. 2. Objectives. In this chapter, you will:. Get to know what uncertain data look like. Explore causes of uncertain data in different applications. Finding Top . k. Most Influential Spatial Facilities over Uncertain Objects. Liming Zhan. Ying Zhang . Wenjie. Zhang . Xuemin. Lin. The . University of New South Wales, . Australia. Outline. Motivation. Andrés Rodríguez-Pose . & . Callum . Wilkie. Session IV: Supporting Lagging regions – Managing Economic Efficiency / Spatial Equity . tradeoffs. The World Bank, Washington, D.C., 29 September 2017. Wherever you roam. And admit that the waters. Around you have grown. And accept it that soon. You'll be drenched to the bone.. If your time to you. Is worth savin'. Then you better start swimmin'. Or you'll sink like a stone. Chapter 2: . Data . Uncertainty Model. 2. Objectives. In this chapter, you will:. Learn the formal definition of uncertain data. Explore different granularities of data uncertainty. Become familiar with different representations of uncertain data. Chapter 1: An Overview of Probabilistic Data Management. 2. Objectives. In this chapter, you will:. Get to know what uncertain data look like. Explore causes of uncertain data in different applications. Chapter 3: Probabilistic Query Answering (1). 2. Objectives. In this chapter, you will:. Learn the challenge of probabilistic query answering on uncertain data. Become familiar with the . framework for probabilistic .