Performance of b-tagging algorithms at the CMS experiment with pp collision data at s\sqrt s=8 TeV

The identification of jets originating from b quarks is crucial both for the searches for new physics and for the measurement of standard model processes. The Compact Muon Solenoid (CMS) collaboration at the Large Hadron Collider (LHC) has developed a variety of algorithms to select b-quark jets based on variables such as the impact parameter of charged particle tracks, properties of reconstructed secondary vertices from heavy hadron decays, and the presence or absence of a lepton in the jet, or combinations thereof. Performance measurements of these b-jet identification algorithms are presented, using multijet and $t\overline{t}$ events recorded in proton-proton collision data at $\sqrt s$=8 TeV with the CMS detector during the LHC Run 1

Model Complexity-Accuracy Trade-off for a Convolutional Neural Network

Convolutional Neural Networks(CNN) has had a great success in the recent past, because of the advent of faster GPUs and memory access. CNNs are really powerful as they learn the features from data in layers such that they exhibit the structure of the V-1 features of the human brain. A huge bottleneck, in this case, is that CNNs are very large and have a very high memory footprint, and hence they cannot be employed on devices with limited storage such as mobile phone, IoT etc. In this work, we study the model complexity versus accuracy trade-off on MNSIT dataset, and give a concrete framework for handling such a problem, given the worst case accuracy that a system can tolerate. In our work, we reduce the model complexity by 236 times, and memory footprint by 19.5 times compared to the base model while achieving worst case accuracy threshold

Trading Away Wide Brands for Cheap Brands

Firms face competing needs to expand product variety and reduce production costs. Trade policy affects firm investments in product variety and production processes differently. Access to larger markets enables innovation to reduce costs. Although firm scale increases, foreign competition reduces markups. Firms react by narrowing their product varieties to recapture these lost markups. I provide a theory detailing this conflicting impact of trade policy and address welfare gains from trade. Accounting for firm heterogeneity, I show support for the theoretical predictions with firm-level innovation data from Thailand's manufacturing sector which experienced unilateral home tariff changes during 2003-2006.brands, trade, manufacturing, heterogeneous firms, Thailand

Face Identification and Clustering

In this thesis, we study two problems based on clustering algorithms. In the first problem, we study the role of visual attributes using an agglomerative clustering algorithm to whittle down the search area where the number of classes is high to improve the performance of clustering. We observe that as we add more attributes, the clustering performance increases overall. In the second problem, we study the role of clustering in aggregating templates in a 1:N open set protocol using multi-shot video as a probe. We observe that by increasing the number of clusters, the performance increases with respect to the baseline and reaches a peak, after which increasing the number of clusters causes the performance to degrade. Experiments are conducted using recently introduced unconstrained IARPA Janus IJB-A, CS2, and CS3 face recognition datasets

Suicide attempts among incarcerated homicide offenders

The aim was to investigate the role of age, drug abuse, period of confinement, loneliness, difficulty in controlling emotions, having no friends in prison, victimization in prison, guilt over crimes, insomnia, nightmares, anxiety, depression, and mood change in predicating suicide attempts in a sample of homicidal young prisoners. Poisson regression model indicated that five variables contributed significantly to the prediction of suicide attempts. Specifically, participants reporting drug abuse, difficulty in controlling emotions, victimization in prison, nightmares, and depression were significantly more likely to report suicide attempts while incarcerated

Time to join the war on the error of plagiarism

A national debate around plagiarism has been sparked in India following accusations made against writer Rajiv Malhotra. Here, Swati Dhingra challenges the notion that plagiarism increases societal welfare. She argues that it is not hard to cite, and that presenting someone else’s work as your own is unegalitarian in the increasingly competitive academic world