qwLSH: Cache-conscious Indexing for Processing Similarity Search Query Workloads in High-Dimensional Spaces

Similarity search queries in high-dimensional spaces are an important type of queries in many domains such as image processing, machine learning, etc. Since exact similarity search indexing techniques suffer from the well-known curse of dimensionality in high-dimensional spaces, approximate search techniques are often utilized instead. Locality Sensitive Hashing (LSH) has been shown to be an effective approximate search method for solving similarity search queries in high-dimensional spaces. Often times, queries in real-world settings arrive as part of a query workload. LSH and its variants are particularly designed to solve single queries effectively. They suffer from one major drawback while executing query workloads: they do not take into consideration important data characteristics for effective cache utilization while designing the index structures. In this paper, we present qwLSH, an index structure for efficiently processing similarity search query workloads in high-dimensional spaces. We intelligently divide a given cache during processing of a query workload by using novel cost models. Experimental results show that, given a query workload, qwLSH is able to perform faster than existing techniques due to its unique cost models and strategies.Comment: Extended version of the published wor

Solid-Phase Microextraction and the Human Fecal VOC Metabolome

The diagnostic potential and health implications of volatile organic compounds (VOCs) present in human feces has begun to receive considerable attention. Headspace solid-phase microextraction (SPME) has greatly facilitated the isolation and analysis of VOCs from human feces. Pioneering human fecal VOC metabolomic investigations have utilized a single SPME fiber type for analyte extraction and analysis. However, we hypothesized that the multifarious nature of metabolites present in human feces dictates the use of several diverse SPME fiber coatings for more comprehensive metabolomic coverage. We report here an evaluation of eight different commercially available SPME fibers, in combination with both GC-MS and GC-FID, and identify the 50/30 µm CAR-DVB-PDMS, 85 µm CAR-PDMS, 65 µm DVB-PDMS, 7 µm PDMS, and 60 µm PEG SPME fibers as a minimal set of fibers appropriate for human fecal VOC metabolomics, collectively isolating approximately 90% of the total metabolites obtained when using all eight fibers. We also evaluate the effect of extraction duration on metabolite isolation and illustrate that ex vivo enteric microbial fermentation has no effect on metabolite composition during prolonged extractions if the SPME is performed as described herein

GC Inlet temperatures per fiber type.

<p>GC Inlet temperatures per fiber type.</p