Gowtham Bellala

TL;DR: A framework, Atlas, which incorporates application-awareness into Software-Defined Networking (SDN), which is currently capable of L2/3/4-based policy enforcement but agnostic to higher layers is presented.

TL;DR: The intent of IoTAbench is to provide the means to perform ``apples-to-apples" comparisons between different sensor data and analytics platforms, and to provide repeatable testing that can be easily extended to multiple IoT use cases.

TL;DR: It is shown that a standard algorithm for object identification, known as generalized binary search, may be viewed as a generalization of Shannon-Fano coding, and this result is extended to the group-based settings, leading to new algorithms.

TL;DR: This paper uses an unsupervised anomaly detection technique based on a low-dimensional embedding to identify power saving opportunities and proposes a semi-supervised approach that combines hidden Markov models (HMM) with standard classifiers such as naive Bayes and support vector machines (SVM).

TL;DR: Measureting cytokine values in bronchoalveolar lavage samples and using bipartite network visualizations with associated quantitative measures to conduct an exploratory analysis of the co-occurrence of cytokines across patients suggest the need to define a molecular-based classification of asthma patients, which could improve the diagnosis and treatment of this disease.