PPT-Efficient Data Presentation

Computer science 2 nd Stage College of Pharmacy Hussein Alsheakh PhD 1 Lecture Objectives Students will be able to Summarizing data in different ways Right graph and table for the right data and audience. FAWN. :. Workloads and Implications. Vijay . Vasudevan. , David Andersen, Michael . Kaminsky. *, Lawrence Tan, . Jason Franklin. , . Iulian. . Moraru. Carnegie Mellon University, *Intel Labs Pittsburgh. Synopticity. Data presentation. Living with earthquakes/hazard perception. Different impacts across the city and amongst different people. Relocating and rebuilding. Changing urban geography in CBD and suburbs. Abstract. With the wide deployment of public cloud computing infrastructures, using clouds to host data query services has become an appealing solution for the advantages on scalability and cost-saving. However, some data might be sensitive that the data owner does not want to move to the cloud unless the data confidentiality and query privacy are guaranteed.. Dell Advanced Infrastructure . Manager. Presenter Name. Title. . Non-strategic tasks burn most cycles. Variable workloads = sub-optimized capacity . We have more physical than virtual servers. Provisioning infrastructure takes too much time. Lee-Ad Gottlieb Hebrew U.. Aryeh Kontorovich Ben Gurion U.. Robert Krauthgamer Weizmann Institute. TexPoint fonts used in EMF. . Read the TexPoint manual before you delete this box.: . A. A. A. A. Objective. Provide a . framework . that can be utilized as a tool for . the advancement of . standardized data presentation. Experimental Design. Instrumentation. Analysis. Presentation. Sample Procurement. November 8, 2016. Stages of Synthesis and Analysis. Collect and organize the data. Make your data manageable.. Mine the data. Identify what you see.. Sort and cluster the data. Manipulate or reframe your data, as necessary.. Baseline (Flightpath D): To be able to . state that the stomach contains acid, state that the liver produces bile and write a simple hypothesis and prediction.. Further (Flightpath C&B ): To be able to . Peter Wittenburg. Max Planck Computing and Data Facility. Overview. brief. . introduction. of . my. . background. re-use. . and . combination. of . data. (. change. . of. . paradigm. in . FAWN. :. Workloads and Implications. Vijay . Vasudevan. , David Andersen, Michael . Kaminsky. *, Lawrence Tan, . Jason Franklin. , . Iulian. . Moraru. Carnegie Mellon University, *Intel Labs Pittsburgh. &. . Energy efficiency Data Protocol and Portal (. EeDaPP. ). &. Energy efficient Mortgage Market Implementation Plan (. EeMMIP. ). In the EU 2. 7. there are… . Bring Energy Efficiency to the EU buildings stock: . Samuli Laine Tero Karras. NVIDIA Research. “Bitmaps” vs “Vectors”. 2. Bitmap 2D image. Vector 2D image. Why Not “Bitmaps” in 3D?. 3. ?. “Bitmap” 3D object. Vector 3D object. Voxel datasets often consist of volume data . MRNet. and GPUs. Evan . Samanas. and Ben . Welton. Density-based clustering. Discovers the number of clusters. Finds oddly-shaped clusters. 2. Mr. Scan: Efficient Clustering with . MRNet. and GPUs. Gyrokinetic. Particle-to-Grid Interpolation for Multicore Processors. Kamesh. . Madduri. , . Samuel Williams. , . Stephane. . Ethier. , . Leonid . Oliker. , John . Shalf. , Erich . Strohmaier. , Katherine Yelick .