A stream processing abstraction framework.

Real-time analysis of large multimedia streams is nowadays made efficient by the existence of several Big Data streaming platforms, like Apache Flink and Samza. However, the use of such platforms is difficult due to the fact that facilities they offer are often too raw to be effectively exploited by analysts. We describe the evolution of RAM3S, a software infrastructure for the integration of Big Data stream processing platforms, to SPAF, an abstraction framework able to provide programmers with a simple but powerful API to ease the development of stream processing applications. By using SPAF, the programmer can easily implement real-time complex analyses of massive streams on top of a distributed computing infrastructure, able to manage the volume and velocity of Big Data streams, thus effectively transforming data into value.

Search and comparison of (epi)genomic feature patterns in multiple genome browser tracks.

BACKGROUND: Genome browsers are widely used for locating interesting genomic regions, but their interactive use is obviously limited to inspecting short genomic portions. An ideal interaction is to provide patterns of regions on the browser, and then extract other genomic regions over the whole genome where such patterns occur, ranked by similarity. RESULTS: We developed SimSearch, an optimized pattern-search method and an open source plugin for the Integrated Genome Browser (IGB), to find genomic region sets that are similar to a given region pattern. It provides efficient visual genome-wide analytics computation in large datasets; the plugin supports intuitive user interactions for selecting an interesting pattern on IGB tracks and visualizing the computed occurrences of similar patterns along the entire genome. SimSearch also includes functions for the annotation and enrichment of results, and is enhanced with a Quickload repository including numerous epigenomic feature datasets from ENCODE and Roadmap Epigenomics. The paper also includes some use cases to show multiple genome-wide analyses of biological interest, which can be easily performed by taking advantage of the presented approach. CONCLUSIONS: The novel SimSearch method provides innovative support for effective genome-wide pattern search and visualization; its relevance and practical usefulness is demonstrated through a number of significant use cases of biological interest. The SimSearch IGB plugin, documentation, and code are freely available at https://deib-geco.github.io/simsearch-app/ and https://github.com/DEIB-GECO/simsearch-app/ .

Automatic detection of cataplexy.

OBJECTIVE: Although being the most specific symptom of narcolepsy type 1 (NT1), cataplexy is currently investigated by clinical interview only, with potential diagnostic pitfalls. Our study aimed at testing the accuracy of an automatic video detection of cataplexy in NT1 patients vs. non-cataplectic subjects undergoing a standardized test with emotional stimulation. METHODS: Fifteen drug-naive NT1 patients and 15 age- and sex-balanced non-cataplectic subjects underwent a standardized video recording procedure including emotional stimulation causing laughter. Video recordings were visually inspected by human scorers to detect three typical cataplexy facial motor patterns (ptosis, mouth opening and head drop), and then analysed by SHIATSU (Semantic-based HIearchical Automatic Tagging of videos by Segmentation using cUts). Expert-based and automatic attack detection was compared in NT1 patients and non-cataplectic subjects. RESULTS: All NT1 patients and none of the non-cataplectic subjects displayed cataplexy during emotional stimulation. Automatic detection correlated well with experts' assessments in NT1 with an overall accuracy of 81%. In non-cataplectic subjects, automatic detection falsely identified cataplexy in two out of 15 (13.3%) subjects who showed active eyes closure during intense laughter as a confounder with ptosis. CONCLUSIONS: Automatic cataplexy detection by applying SHIATSU to a standardized test for video documentation of cataplexy is feasible, with an overall accuracy of 81% compared to human examiners. Further studies are warranted to enlarge the range of elementary motor patterns detected, analyse their temporal/spatial relations and quantify cataplexy for diagnostic purposes.

WARP: accurate retrieval of shapes using phase of fourier descriptors and time warping distance.

Effective and efficient retrieval of similar shapes from large image databases is still a challenging problem in spite of the high relevance that shape information can have in describing image contents. In this paper, we propose a novel Fourier-based approach, called WARP, for matching and retrieving similar shapes. The unique characteristics of WARP are the exploitation of the phase of Fourier coefficients and the use of the Dynamic Time Warping (DTW) distance to compare shape descriptors. While phase information provides a more accurate description of object boundaries than using only the amplitude of Fourier coefficients, the DTW distance permits us to accurately match images even in the presence of (limited) phase shiftings. In terms of classical precision/recall measures, we experimentally demonstrate that WARP can gain, say, up to 35 percent in precision at a 20 percent recall level with respect to Fourier-based techniques that use neither phase nor DTW distance.