Impact Factor 3.582 Case Studies Journal ISSN (2305-509X) – Volume 4, Issue 7 – July-2015 Maggi Stews in Lead and MSG Pot: Controversy over India’s favourite instant Noodles Author Details: Dr. Ramesh Sardar (Associate Professor) School of Management Studies, North Maharashtra University, Jalgaon (M.S) Abstract The Maggi imbroglio escalated to an unprecedented level with India's food regulator Food Safety and Standards Authority of India (FSSAI) ordering a total recall of all nine variants of the
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RESEARCH ARTICLE REVIEW Vol.3 Issue 1, January-March 2010 ISSN 0974-2441 Nutraceuticals: new era of medicine and health Manisha Pandey *, Rohit K Verma, Shubhini A Saraf Department of Pharmaceutics, Babu Banarasi Das National Institute of Technology and Management, Lucknow, Uttar Pradesh – 227105, India. Address for correspondence: Manisha Pandey, Department of Pharmaceutics, Babu Banarasi Das National Institute of Technology and Management, Lucknow, Uttar Pradesh – 227105, India.
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large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed
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De-Identified Personal Health Care System Using Hadoop The use of medical Big Data is increasingly popular in health care services and clinical research. The biggest challenges in health care centers are the huge amount of data flows into the systems daily. Crunching this BigData and de-identifying it in a traditional data mining tools had problems. Therefore to provide solution to the de-identifying personal health information, Map Reduce application uses jar files which contain a combination
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variant to different light conditions and other influences. To implement this approach we have utilized a simple web cam which is working on 20 fps with 7 mega pixel intensity. On having the input sequence of images through web cam it uses some pre-processing steps for removal of background noise and employs K-means clustering for segmenting the hand object from rest of the background, so that only segmented significant cluster or hand object is to be processed in order to calculate shape based features
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------------------------------------------------- UNIVERSITI UTARA MALAYSIA ------------------------------------------------- BPMN6023 ------------------------------------------------- STRATEGIC MANAGEMENT ------------------------------------------------- GROUP PROJECT: FAIRY FOOD PROCESSING SDN. BHD. PREPARED FOR: DR DARWINA AHMAD ARSHAD PREPARED BY: 1. WAN UMMU HANUNI BINTI WAN DIN 813632 2. YANG HUAI 815173 3. ZHANG YAN 815174 4. SALH AGRERAH ALI 815030 5. KHALID GADHWARA EMHEMED 815023 SUBMISSION DATE: 7th
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Table of Contents 1. Company Background 2. Industry Research * Competitors * Suppliers * Economic Conditions * Industry Trends * Regulations 3. SWOT & Environmental Scanning 4. Greentraks Analysis 5. References 6. Table of Addendums 1. COMPANY BACKGROUND Burgers and Brew is an innovative chain that is unlike any other restaurant in Chico. The first Burgers and Brew was established in 2000. The Chico location has been here since 2010 and is located in the historic
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Assignment: Publix Case StudyCERTIFICATION OF AUTHORSHIP: I certify that I am the author of this paper and that any assistance I received in its preparation is fully acknowledged and disclosed in the paper. I have also cited any sources from which I used data, ideas or words, either quoted directly or paraphrased. I also certify that this paper was prepared by me specifically for this course.Student’s Signature: Kaley AguirreInstructor’s Grade on Assignment:Instructor’s Comments: | | CVF Question 1:
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7 5.3. Lets collaborate! 7 5.4. Consumer evolution 8 6. Research plan 9 6.1. Description of research subjects and design 9 6.2. Sampling plan 9 6.3. Instruments 9 6.4. Procedures 9 7. Proposed methods for processing, analysing and interpreting data 11 7.1. Quantitative 11 7.2. Qualitative 11 8. Timeline 12 9. Potential outcomes and conclusion 13 10. Reference list 14 11. Appendix A 15 Background * Green marketing is the product modifications and/or
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HIPI: A Hadoop Image Processing Interface for Image-based MapReduce Tasks Chris Sweeney Liu Liu Sean Arietta Jason Lawrence University of Virginia Images 1...k Cull ... ... images n-k....n Hipi Image Bundle Map 1 Map i Reduce 1 Shuffle ... Result Reduce j Figure 1: A typical MapReduce pipeline using our Hadoop Image Processing Interface with n images, i map nodes, and j reduce nodes Abstract 1 The amount of images being uploaded to
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