Givemore Dube - Denhe.info Presentation

May 23, 2014Download as PPTX, PDF0 likes490 views

Richwell Phinias

Givemore Dube Presentation on Denhe.info at the Computer Society of Zimbabwe, Emerging Technology Entrepreneurs Series

www.denhe.info
utande hwezivo mumasaisai
naManjenje Ganda Ravasikana,
nemukunda wekwaMheta

• kukotsvera ruzivo
• kushambadza kukosha kweruzvivo rwedu
• kuchengetedza nokudzidza zvedu
• kususukidza ruzivo rwedu
• kuwana raramo kubva muruzivo
• kuvamba mhare kubva munezvedu

1. Vakotsveri 3. Vamhare
4. Vashandisi
2. denhe
dzidzo umhizha tsika magariro nhakamitauro

2007
2012
2013
2014
Bvunzo Gwaro 7(ZIMSEC)
Munhu wese

Iwe neni tiriparwendo
chirongwa chekuvandudza upfumi ndechedu
Rwizi runokura nezvikova

- The document discusses security concerns around using cloud computing for online exams, specifically Jordan's General Associate Degree Examination (SHAMEL). - It outlines the legacy exam system and proposes a new cloud-based system to reduce costs and security risks. The proposed system would divide data handling between instructors, exam managers, and students and encrypt data before storing it in the cloud. - The goal is to allow exam data to be securely stored in the cloud while avoiding piracy and reducing costs and time compared to encrypting data locally.

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Vyhledávače zboží 2014: PricemaniaBESTETO

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A ROUTING MECHANISM BASED ON SOCIAL NETWORKS AND BETWEENNESS CENTRALITY IN DE...ijcsit

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Top 7 hr generalist interview questions answersjob-interview-questions

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Thong tin Can ho Celadon City Tan Phu. Hotline: 0985 889 990, http://canhosai...TTC Land

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MULTI-PARAMETER BASED PERFORMANCE EVALUATION OF CLASSIFICATION ALGORITHMSijcsit

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Diabetes disease is amongst the most common disease in India. It affects patient’s health and also leads to other chronic diseases. Prediction of diabetes plays a significant role in saving of life and cost. Predicting diabetes in human body is a challenging task because it depends on several factors. Few studies have reported the performance of classification algorithms in terms of accuracy. Results in these studies are difficult and complex to understand by medical practitioner and also lack in terms of visual aids as they arepresented in pure text format. This reported survey uses ROC and PRC graphical measures toimproveunderstanding of results. A detailed parameter wise discussion of comparison is also presented which lacksin other reported surveys. Execution time, Accuracy, TP Rate, FP Rate, Precision, Recall, F Measureparameters are used for comparative analysis and Confusion Matrix is prepared for quick review of each algorithm. Ten fold cross validation method is used for estimation of prediction model. Different sets of classification algorithms are analyzed on diabetes dataset acquired from UCI repository

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