62 research outputs found
On K-Means Cluster Preservation using Quantization Schemes
This work examines under what conditions compression methodologies can retain the outcome of clustering operations. We focus on the popular k-Means clustering algorithm and we demonstrate how a properly constructed compression scheme based on post-clustering quantization is capable of maintaining the global cluster structure. Our analytical derivations indicate that a 1-bit moment preserving quantizer per cluster is sufficient to retain the original data clusters. Merits of the proposed compression technique include: a) reduced storage requirements with clustering guarantees, b) data privacy on the original values, and c) shape preservation for data visualization purposes. We evaluate quantization scheme on various high-dimensional datasets, including 1-dimensional and 2-dimensional timeseries (shape datasets) and demonstrate the cluster preservation property. We also compare with previously proposed simplification techniques in the time-series area and show significant improvements both on the clustering and shape preservation of the compressed datasets.
Online Pairing of VoIP Conversations
This paper answers the following question; given a multiplicity of evolving 1-way conversations, can a machine or an algorithm discern the conversational pairs in an online fashion, without understanding the content of the communications? Our analysis indicates that this is possible, and can be achieved just by exploiting the temporal dynamics inherent in a conversation. We also show that our findings are applicable for anonymous and encrypted conversations over VoIP networks. We achieve this by exploiting the aperiodic inter-departure time of VoIP packets, hence trivializing each VoIP stream into a binary time-series, indicating the voice activity of each stream. We propose effective techniques that progressively pair conversing parties with high accuracy and in a limited amount of time. Our findings are verified empirically on a dataset consisting of 1000 conversations. We obtain very high pairing accuracy that reaches 97 % after 5 minutes of voice conversations. Using a modeling approach we also demonstrate analytically that our result can be extended over an unlimited number of conversations
Measurement of pleural pressure swings with a fluid-filled esophageal catheter vs pulmonary artery occlusion pressure
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