Applied Time Series Analysis and Innovative Computing

Ao, Sio-Iong

doi:10.1007/978-90-481-8768-3

Cited by 17 publications

(16 citation statements)

References 1 publication

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“…Spectral analysis was performed to detect periodicity in the total larval abundance indices of snow crab, toad crabs and rock crab. Abundance indices were smoothed using locally weighted regression (LOESS) prior to analysis to reduce random noise and make long‐term fluctuations stand out more clearly (Ao, ). We first calculated the Lomb–Scargle periodogram, which produces better results on unevenly spaced data (i.e.…”

Section: Methodsmentioning

confidence: 99%

Long‐term trends and drivers of larval phenology and abundance of dominant brachyuran crabs in the Gulf of St. Lawrence (Canada)

Emond

Sainte‐Marie

Bêty

2020

Fisheries Oceanography

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Climate change has led to major shifts in the timing of biological events, with many studies demonstrating earlier phenology in response to warming. However, few of these studies have investigated the effects of climate change on the phenology of larvae in marine species. Phenological shifts can result in mismatches between consumers and prey and hence affect growth and survival of individuals, and ultimately population demography. We investigated the temporal changes in phenology and abundance of the larvae of dominant brachyuran crabs in the southern Gulf of St. Lawrence (eastern Canada) based on plankton collections spanning 1982–2012. The Gulf of St. Lawrence has warmed since the early 1990s, and our analyses revealed that larvae of snow crab (Chionoecetes opilio) and toad crabs (Hyas spp.) exhibited a significant trend towards earlier phenology over the 30‐year study period. This shift in phenology appeared to be a consequence of the effect of climate warming on both the timing of hatching and larval development rate. Larval abundance responded differently by crab taxon to climate warming, likely due to differences in thermal tolerance. The warming trend was unfavourable to snow crab, which is the most cold‐adapted and stenothermic of the taxa examined in this study. The abundance of snow crab larvae was lower when sea ice retreat occurred earlier than day 110 of the year and sea surface temperature was higher than 8.5°C. On the other hand, larval abundance of rock crab (Cancer irroratus), which prefers higher temperatures, was positively related to surface temperature.

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Section: Methodsmentioning

confidence: 99%

Long‐term trends and drivers of larval phenology and abundance of dominant brachyuran crabs in the Gulf of St. Lawrence (Canada)

Emond

Sainte‐Marie

Bêty

2020

Fisheries Oceanography

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“…In modelling any multidimensional feature such as the objects' location, multivariate AR modelling [9] techniques are utilized to capture parallel dependencies across feature dimensions.…”

Section: A Dynamical Modellingmentioning

confidence: 99%

Video event classification and anomaly identification using spectral clustering

Fernando

Perera

Herath

et al. 2015

2015 Fifteenth International Conference on Advances in ICT for Emerging Regions (ICTer)

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This paper proposes a spectral clustering based methodology to classify video events and to detect anomalies. Feature trajectories from objects in a video are modelled, compared and clustered in order to classify the detected object events. Principles of normalized spectral clustering are used with modifications to affinity structure. A novel method for determining spectral clustering parameters based on Eigen structure of the affinity matrix is introduced. Employment of unsupervised learning for event classification is made possible by the proposed successive cluster identity labelling algorithm. A mechanism to identify abnormal events under the context is also introduced. The effectiveness and the robustness of the proposed methodology are demonstrated through experiments conducted on video streams focusing on human motion patterns.

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“…However, these measures preserve many but not all of the important properties of a given time series. Therefore, there is considerable research toward the identification of metrics that can capture the additional information or quantify time series in a completely new ways 26 27 28 29 .…”

Section: Time Series To Networkmentioning

confidence: 99%

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

Banerjee

Azharuddin

Sen

et al. 2015

Sci Rep

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We present a fresh and broad yet simple approach towards information retrieval in general and diagnostics in particular by applying the theory of complex networks on multidimensional, dynamic images. We demonstrate a successful use of our method with the time series generated from high content thermal imaging videos of patients suffering from the aqueous deficient dry eye (ADDE) disease. Remarkably, network analyses of thermal imaging time series of contact lens users and patients upon whom Laser-Assisted in situ Keratomileusis (Lasik) surgery has been conducted, exhibit pronounced similarity with results obtained from ADDE patients. We also propose a general framework for the transformation of multidimensional images to networks for futuristic biometry. Our approach is general and scalable to other fluctuation-based devices where network parameters derived from fluctuations, act as effective discriminators and diagnostic markers.

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Applied Time Series Analysis and Innovative Computing

Cited by 17 publications

References 1 publication

Long‐term trends and drivers of larval phenology and abundance of dominant brachyuran crabs in the Gulf of St. Lawrence (Canada)

Long‐term trends and drivers of larval phenology and abundance of dominant brachyuran crabs in the Gulf of St. Lawrence (Canada)

Video event classification and anomaly identification using spectral clustering

Using complex networks towards information retrieval and diagnostics in multidimensional imaging

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