Jadran Sessa
Masdar Institute of Science and Technology
5 Papers
3 Citations
Jadran Sessa is an academic researcher from Masdar Institute of Science and Technology. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 2, co-authored 2 publications.
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Papers
Techniques to deal with missing data
Jadran Sessa,Dabeeruddin Syed +1 more
- 01 Dec 2016
TL;DR: This work has compared two imputation methods for dealing with the missing data, namely k-NN imputation method and mean and median imputations method, and found that both of the imputations are efficient and yield more or less the same accuracy.
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Authorization schemes for internet of things: requirements, weaknesses, future challenges and trends
TL;DR: In this paper , the authors provide a comprehensive comparative analysis of the current state-of-the-art IoT authorization schemes to highlight their strengths and weaknesses, and highlight the most important requirements and highlights the authorization threats and weaknesses impacting authorization in the IoT.
Intelligent Automation of Crime Prediction using Data Mining
Abdullah Alghushami,Dabeeruddin Syed,Jadran Sessa,Ameema Zainab +3 more
- 01 Jun 2022
TL;DR: This paper compares machine learning algorithms namely naive Bayes, bayesian networks, weighted k-nearest neighbors, multi-layer perceptron classifier, guassian naive bayes, decision tree, random forest, adaboost, gradient boosting, linear discriminant analysis and quadratic discriminate analysis for crime category identification and crime prediction.
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Data Analysis of Correlation Between Project Popularity and Code Change Frequency
Dabeeruddin Syed,Jadran Sessa,Andreas Henschel,Davor Svetinovic +3 more
- 16 Oct 2016
TL;DR: It is found that projects with at least 1500 watchers each month have a strong positive correlation between the project popularity and frequency of code changes, and the number of pull requests is 73.2 % more important to the popularity of a project than thenumber of watchers.
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Towards heat tolerant metagenome functional prediction, coral microbial community composition, and enrichment analysis
TL;DR: In this article , the authors analyzed the overall microbial community composition of different coral species found in the Australian waters and identified the most abundant Operational Taxonomic Units (OTUs) on different taxonomic levels.
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