Machine Learning has been steadily gaining traction for its use in Anomaly-based Network Intrusion Detection Systems (A-NIDS). Research into this domain is frequently performed using the KDD CUP 99 dataset as a benchmark. Several studies question its usability while constructing a contemporary NIDS, due to the skewed response distribution, nonstationarity, and failure to incorporate modern attacks. In this paper, we compare the performance for KDD-99 alternatives when trained using classification models commonly found in literature: Neural Network, Support Vector Machine, Decision Tree, Random Forest, Naive Bayes and K-Means. Applying the SMOTE oversampling technique and random undersampling, we create a balanced version of NSL-KDD and prove that skewed target classes in KDD-99 and NSL-KDD hamper the efficacy of classifiers on minority classes (U2R and R2L), leading to possible security risks. We explore UNSW-NB15, a modern substitute to KDD-99 with greater uniformity of pattern distribution. We benchmark this dataset before and after SMOTE oversampling to observe the effect on minority performance. Our results indicate that classifiers trained on UNSW-NB15 match or better the Weighted F1-Score of those trained on NSL-KDD and KDD-99 in the binary case, thus advocating UNSW-NB15 as a modern substitute to these datasets.

This is an illustrative note on application of Foster Greer Thorbecke (FGT) criterion to measurement and comparison of undernourishment among children. Given the semblance between head-count measure of poverty and measuring undernourishment among children, there arises a need for application of FGT criterion in assessment of undernourishment as well. This not only helps in assessing intensity and inequality aspect but also can adjust the head count accounting for both to make a valid comparison on levels of undernourishment across situations.

Drug prices and cost of healthcare are two major concerns globally. This entails to examine the structure and performance of domestic pharmaceutical industry and Indian market’s pricing policy of drugs. This article contributes to the debate around regulation of drug prices in India from the perspectives of the healthcare of the poor and affordability.

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The paper examines the impact of the initiative taken by a non-government organization—Self-Employed Women’s Association (SEWA)—in Ahmedabad, a city in western India to impart knowledge about sexual and reproductive health to adolescent girls. Quasi-experimental design was used for data collection from beneficiary and non-beneficiary households in two rural blocks and two cities of Gujarat. Non-beneficiary households from control areas were selected with similar socio-economic characteristics. The study noted that the girls from control areas were not much different with respect to awareness about reproductive and sexual health compared to those who were exposed to training imparted by SEWA. While the girls who participated in health training received information on menstrual hygiene, their household situation was not always conducive to allow them to practice what was taught. Girls were keen to learn about what is safe sex or how to deal if confronted with difficult boy–girl interaction. The need to include discussion on such issues with young girls is evident and timely. Any intervention to improve the conditions of adolescent girls cannot be limited to providing information about hygiene or giving additional nutritional supplement (as is done in the government centres), but it is important to create a space for them to express their concerns. Also, there is a need for interaction with parents to make them sensitive towards health of their young girls and help them pursue their goals.