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Predictors of obesity among post graduate trainee doctors working in a tertiary care hospital of public sector in Karachi, Pakistan.
OBJECTIVES To identify the predictors of obesity among post graduate trainee doctors working in a tertiary care hospital of public sector at Karachi, Pakistan. METHODS A cross sectional analyticalExpand
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Machine Learning Techniques for Intrusion Detection: A Comparative Analysis
TLDR
Weka is a machine learning-based intrusion detection system that learns with experience, has improved performance in the situations they have already encountered. Expand
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Wavelet neural network model for network intrusion detection system
TLDR
In this study, a hybrid method based on coupling Discrete Wavelet Transforms and Artificial Neural Network (ANN) for Intrusion Detection is proposed. Expand
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Benchmark Datasets for Network Intrusion Detection: A Review
TLDR
In this work, we intend to provide a thorough review of the benchmark datasets available for Network Intrusion Detection (NID) which researchers in the field can use to train and test their models. Expand
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Feature selection techniques for intrusion detection using non-bio-inspired and bio-inspired optimization algorithms
TLDR
A survey of feature selection techniques for IDS, including bio-inspired and non-bio-inspired algorithms. Expand
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A Fusion of Feature Extraction and Feature Selection Technique for Network Intrusion Detection
TLDR
With varied and widespread attacks on information systems, intrusion detection systems (IDS) have become an indispensable part of security policy for protecting data. Expand
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Peri-Urbanism in Globalizing India: A Study of Pollution, Health and Community Awareness
This paper examines the intersection between environmental pollution and people’s acknowledgements of, and responses to, health issues in Karhera, a former agricultural village situated between theExpand
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An Improvised k-NN Respecting Diversity of Data for Network Intrusion Detection
TLDR
We have applied Synthetic Minority Oversampling Technique (SMOTE) to balance the dataset and eliminate the skewness of the class distribution. Expand
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Large-scale nonlinear dimensionality reduction for network intrusion detection
TLDR
We combine classification with recent and scalable nonlinear dimensionality reduction (NLDR) methods like $t$-SNE to get 3D embeddings. Expand