28,937 research outputs found
Learning sound representations using trainable COPE feature extractors
Sound analysis research has mainly been focused on speech and music
processing. The deployed methodologies are not suitable for analysis of sounds
with varying background noise, in many cases with very low signal-to-noise
ratio (SNR). In this paper, we present a method for the detection of patterns
of interest in audio signals. We propose novel trainable feature extractors,
which we call COPE (Combination of Peaks of Energy). The structure of a COPE
feature extractor is determined using a single prototype sound pattern in an
automatic configuration process, which is a type of representation learning. We
construct a set of COPE feature extractors, configured on a number of training
patterns. Then we take their responses to build feature vectors that we use in
combination with a classifier to detect and classify patterns of interest in
audio signals. We carried out experiments on four public data sets: MIVIA audio
events, MIVIA road events, ESC-10 and TU Dortmund data sets. The results that
we achieved (recognition rate equal to 91.71% on the MIVIA audio events, 94% on
the MIVIA road events, 81.25% on the ESC-10 and 94.27% on the TU Dortmund)
demonstrate the effectiveness of the proposed method and are higher than the
ones obtained by other existing approaches. The COPE feature extractors have
high robustness to variations of SNR. Real-time performance is achieved even
when the value of a large number of features is computed.Comment: Accepted for publication in Pattern Recognitio
Ontologies and Information Extraction
This report argues that, even in the simplest cases, IE is an ontology-driven
process. It is not a mere text filtering method based on simple pattern
matching and keywords, because the extracted pieces of texts are interpreted
with respect to a predefined partial domain model. This report shows that
depending on the nature and the depth of the interpretation to be done for
extracting the information, more or less knowledge must be involved. This
report is mainly illustrated in biology, a domain in which there are critical
needs for content-based exploration of the scientific literature and which
becomes a major application domain for IE
Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations
Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions
Intelligent Management and Efficient Operation of Big Data
This chapter details how Big Data can be used and implemented in networking
and computing infrastructures. Specifically, it addresses three main aspects:
the timely extraction of relevant knowledge from heterogeneous, and very often
unstructured large data sources, the enhancement on the performance of
processing and networking (cloud) infrastructures that are the most important
foundational pillars of Big Data applications or services, and novel ways to
efficiently manage network infrastructures with high-level composed policies
for supporting the transmission of large amounts of data with distinct
requisites (video vs. non-video). A case study involving an intelligent
management solution to route data traffic with diverse requirements in a wide
area Internet Exchange Point is presented, discussed in the context of Big
Data, and evaluated.Comment: In book Handbook of Research on Trends and Future Directions in Big
Data and Web Intelligence, IGI Global, 201
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