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Open AccessArticle Temporal Shape Changes and Future Trends in European Automotive Design
Machines 2015, 3(3), 256-267; doi:10.3390/machines3030256
Received: 13 May 2015 / Revised: 27 August 2015 / Accepted: 7 September 2015 / Published: 17 September 2015
Cited by 1 | Viewed by 748 | PDF Full-text (776 KB) | HTML Full-text | XML Full-text
Abstract
Evolution produces genuine novelty in morphology through the selection of competing designs as phenotypes. When applied to human creativity, the evolutionary paradigm can provide insight into the ways that our technology and its design are modified through time. The shape of European utilitarian
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Evolution produces genuine novelty in morphology through the selection of competing designs as phenotypes. When applied to human creativity, the evolutionary paradigm can provide insight into the ways that our technology and its design are modified through time. The shape of European utilitarian cars in the past 60 years was analyzed in order to determine whether changes occur in a gradual fashion or through saltation, clarifying which are the more conserved and more variable parts of the designs. We also attempted to predict the future appearances of the cars within the next decade, discussing all results within the framework of relevant evolutionary-like equivalences. Here, we analyzed the modification in the shape of European utilitarian cars in the past 60 years by three-dimensional geometric morphometrics to test whether these changes occurred in a gradual or more saltatory fashion. The geometric morphometric shape analysis showed that even though car brands have always been preserving distinct shapes, all followed a gradual pattern of evolution which is now converging toward a more similar fusiform and compact asset. This process was described using Darwinian evolution as a metaphor to quantify and interpret changes over time and the societal pressures promoting them. Full article
Open AccessArticle A New Colorimetrically-Calibrated Automated Video-Imaging Protocol for Day-Night Fish Counting at the OBSEA Coastal Cabled Observatory
Sensors 2013, 13(11), 14740-14753; doi:10.3390/s131114740
Received: 30 August 2013 / Revised: 22 October 2013 / Accepted: 22 October 2013 / Published: 30 October 2013
Cited by 4 | Viewed by 1651 | PDF Full-text (747 KB) | HTML Full-text | XML Full-text
Abstract
Field measurements of the swimming activity rhythms of fishes are scant due to the difficulty of counting individuals at a high frequency over a long period of time. Cabled observatory video monitoring allows such a sampling at a high frequency over unlimited periods
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Field measurements of the swimming activity rhythms of fishes are scant due to the difficulty of counting individuals at a high frequency over a long period of time. Cabled observatory video monitoring allows such a sampling at a high frequency over unlimited periods of time. Unfortunately, automation for the extraction of biological information (i.e., animals’ visual counts per unit of time) is still a major bottleneck. In this study, we describe a new automated video-imaging protocol for the 24-h continuous counting of fishes in colorimetrically calibrated time-lapse photographic outputs, taken by a shallow water (20 m depth) cabled video-platform, the OBSEA. The spectral reflectance value for each patch was measured between 400 to 700 nm and then converted into standard RGB, used as a reference for all subsequent calibrations. All the images were acquired within a standardized Region Of Interest (ROI), represented by a 2 × 2 m methacrylate panel, endowed with a 9-colour calibration chart, and calibrated using the recently implemented “3D Thin-Plate Spline” warping approach in order to numerically define color by its coordinates in n-dimensional space. That operation was repeated on a subset of images, 500 images as a training set, manually selected since acquired under optimum visibility conditions. All images plus those for the training set were ordered together through Principal Component Analysis allowing the selection of 614 images (67.6%) out of 908 as a total corresponding to 18 days (at 30 min frequency). The Roberts operator (used in image processing and computer vision for edge detection) was used to highlights regions of high spatial colour gradient corresponding to fishes’ bodies. Time series in manual and visual counts were compared together for efficiency evaluation. Periodogram and waveform analysis outputs provided very similar results, although quantified parameters in relation to the strength of respective rhythms were different. Results indicate that automation efficiency is limited by optimum visibility conditions. Data sets from manual counting present the larger day-night fluctuations in comparison to those derived from automation. This comparison indicates that the automation protocol subestimate fish numbers but it is anyway suitable for the study of community activity rhythms. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle RGB Color Calibration for Quantitative Image Analysis: The “3D Thin-Plate Spline” Warping Approach
Sensors 2012, 12(6), 7063-7079; doi:10.3390/s120607063
Received: 12 April 2012 / Revised: 14 May 2012 / Accepted: 22 May 2012 / Published: 29 May 2012
Cited by 23 | Viewed by 3179 | PDF Full-text (389 KB) | HTML Full-text | XML Full-text
Abstract
In the last years the need to numerically define color by its coordinates in n-dimensional space has increased strongly. Colorimetric calibration is fundamental in food processing and other biological disciplines to quantitatively compare samples’ color during workflow with many devices. Several software programmes
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In the last years the need to numerically define color by its coordinates in n-dimensional space has increased strongly. Colorimetric calibration is fundamental in food processing and other biological disciplines to quantitatively compare samples’ color during workflow with many devices. Several software programmes are available to perform standardized colorimetric procedures, but they are often too imprecise for scientific purposes. In this study, we applied the Thin-Plate Spline interpolation algorithm to calibrate colours in sRGB space (the corresponding Matlab code is reported in the Appendix). This was compared with other two approaches. The first is based on a commercial calibration system (ProfileMaker) and the second on a Partial Least Square analysis. Moreover, to explore device variability and resolution two different cameras were adopted and for each sensor, three consecutive pictures were acquired under four different light conditions. According to our results, the Thin-Plate Spline approach reported a very high efficiency of calibration allowing the possibility to create a revolution in the in-field applicative context of colour quantification not only in food sciences, but also in other biological disciplines. These results are of great importance for scientific color evaluation when lighting conditions are not controlled. Moreover, it allows the use of low cost instruments while still returning scientifically sound quantitative data. Full article
(This article belongs to the Section Physical Sensors)
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Open AccessArticle The New Pelagic Operational Observatory of the Catalan Sea (OOCS) for the Multisensor Coordinated Measurement of Atmospheric and Oceanographic Conditions
Sensors 2011, 11(12), 11251-11272; doi:10.3390/s111211251
Received: 8 October 2011 / Revised: 7 November 2011 / Accepted: 18 November 2011 / Published: 28 November 2011
Cited by 9 | Viewed by 3839 | PDF Full-text (1854 KB) | HTML Full-text | XML Full-text
Abstract
The new pelagic Operational Observatory of the Catalan Sea (OOCS) for the coordinated multisensor measurement of atmospheric and oceanographic conditions has been recently installed (2009) in the Catalan Sea (41°39'N, 2°54'E; Western Mediterranean) and continuously operated (with minor maintenance gaps) until today. This
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The new pelagic Operational Observatory of the Catalan Sea (OOCS) for the coordinated multisensor measurement of atmospheric and oceanographic conditions has been recently installed (2009) in the Catalan Sea (41°39'N, 2°54'E; Western Mediterranean) and continuously operated (with minor maintenance gaps) until today. This multiparametric platform is moored at 192 m depth, 9.3 km off Blanes harbour (Girona, Spain). It is composed of a buoy holding atmospheric sensors and a set of oceanographic sensors measuring the water conditions over the upper 100 m depth. The station is located close to the head of the Blanes submarine canyon where an important multispecies pelagic and demersal fishery gives the station ecological and economic relevance. The OOCS provides important records on atmospheric and oceanographic conditions, the latter through the measurement of hydrological and biogeochemical parameters, at depths with a time resolution never attained before for this area of the Mediterranean. Twenty four moored sensors and probes operating in a coordinated fashion provide important data on Essential Ocean Variables (EOVs; UNESCO) such as temperature, salinity, pressure, dissolved oxygen, chlorophyll fluorescence, and turbidity. In comparison with other pelagic observatories presently operating in other world areas, OOCS also measures photosynthetic available radiation (PAR) from above the sea surface and at different depths in the upper 50 m. Data are recorded each 30 min and transmitted in real-time to a ground station via GPRS. This time series is published and automatically updated at the frequency of data collection on the official OOCS website (http://www.ceab.csic.es/~oceans). Under development are embedded automated routines for the in situ data treatment and assimilation into numerical models, in order to provide a reliable local marine processing forecast. In this work, our goal is to detail the OOCS multisensor architecture in relation to the coordinated capability for the remote, continuous and prolonged monitoring of atmospheric and oceanographic conditions, including data communication and storage. Accordingly, time series of measurements for a number of biological parameters will be presented for the summer months of 2011. Marine hindcast outputs from the numerical models implemented for simulating the conditions over the study area are shown. The strong changes of atmospheric conditions recorded in the last years over the area have altered the marine conditions of living organisms, but the dimension of the impact remains unclear. The OOCS multisensor coordinated monitoring has been specifically designed to address this issue, thus contributing to better understand the present environmental fluctuations and to provide a sound basis for a more accurate marine forecast system. Full article
(This article belongs to the Special Issue Collaborative Sensors)
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Open AccessArticle Automated Image Analysis for the Detection of Benthic Crustaceans and Bacterial Mat Coverage Using the VENUS Undersea Cabled Network
Sensors 2011, 11(11), 10534-10556; doi:10.3390/s111110534
Received: 4 July 2011 / Revised: 8 October 2011 / Accepted: 1 November 2011 / Published: 4 November 2011
Cited by 14 | Viewed by 3535 | PDF Full-text (1985 KB) | HTML Full-text | XML Full-text
Abstract
The development and deployment of sensors for undersea cabled observatories is presently biased toward the measurement of habitat variables, while sensor technologies for biological community characterization through species identification and individual counting are less common. The VENUS cabled multisensory network (Vancouver Island, Canada)
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The development and deployment of sensors for undersea cabled observatories is presently biased toward the measurement of habitat variables, while sensor technologies for biological community characterization through species identification and individual counting are less common. The VENUS cabled multisensory network (Vancouver Island, Canada) deploys seafloor camera systems at several sites. Our objective in this study was to implement new automated image analysis protocols for the recognition and counting of benthic decapods (i.e., the galatheid squat lobster, Munida quadrispina), as well as for the evaluation of changes in bacterial mat coverage (i.e., Beggiatoa spp.), using a camera deployed in Saanich Inlet (103 m depth). For the counting of Munida we remotely acquired 100 digital photos at hourly intervals from 2 to 6 December 2009. In the case of bacterial mat coverage estimation, images were taken from 2 to 8 December 2009 at the same time frequency. The automated image analysis protocols for both study cases were created in MatLab 7.1. Automation for Munida counting incorporated the combination of both filtering and background correction (Median- and Top-Hat Filters) with Euclidean Distances (ED) on Red-Green-Blue (RGB) channels. The Scale-Invariant Feature Transform (SIFT) features and Fourier Descriptors (FD) of tracked objects were then extracted. Animal classifications were carried out with the tools of morphometric multivariate statistic (i.e., Partial Least Square Discriminant Analysis; PLSDA) on Mean RGB (RGBv) value for each object and Fourier Descriptors (RGBv+FD) matrices plus SIFT and ED. The SIFT approach returned the better results. Higher percentages of images were correctly classified and lower misclassification errors (an animal is present but not detected) occurred. In contrast, RGBv+FD and ED resulted in a high incidence of records being generated for non-present animals. Bacterial mat coverage was estimated in terms of Percent Coverage and Fractal Dimension. A constant Region of Interest (ROI) was defined and background extraction by a Gaussian Blurring Filter was performed. Image subtraction within ROI was followed by the sum of the RGB channels matrices. Percent Coverage was calculated on the resulting image. Fractal Dimension was estimated using the box-counting method. The images were then resized to a dimension in pixels equal to a power of 2, allowing subdivision into sub-multiple quadrants. In comparisons of manual and automated Percent Coverage and Fractal Dimension estimates, the former showed an overestimation tendency for both parameters. The primary limitations on the automatic analysis of benthic images were habitat variations in sediment texture and water column turbidity. The application of filters for background corrections is a required preliminary step for the efficient recognition of animals and bacterial mat patches. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle A New Laboratory Radio Frequency Identification (RFID) System for Behavioural Tracking of Marine Organisms
Sensors 2011, 11(10), 9532-9548; doi:10.3390/s111009532
Received: 12 September 2011 / Revised: 7 October 2011 / Accepted: 9 October 2011 / Published: 11 October 2011
Cited by 20 | Viewed by 4630 | PDF Full-text (860 KB) | HTML Full-text | XML Full-text
Abstract
Radio frequency identification (RFID) devices are currently used to quantify several traits of animal behaviour with potential applications for the study of marine organisms. To date, behavioural studies with marine organisms are rare because of the technical difficulty of propagating radio waves within
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Radio frequency identification (RFID) devices are currently used to quantify several traits of animal behaviour with potential applications for the study of marine organisms. To date, behavioural studies with marine organisms are rare because of the technical difficulty of propagating radio waves within the saltwater medium. We present a novel RFID tracking system to study the burrowing behaviour of a valuable fishery resource, the Norway lobster (Nephrops norvegicus L.). The system consists of a network of six controllers, each handling a group of seven antennas. That network was placed below a microcosm tank that recreated important features typical of Nephrops’ grounds, such as the presence of multiple burrows. The animals carried a passive transponder attached to their telson, operating at 13.56 MHz. The tracking system was implemented to concurrently report the behaviour of up to three individuals, in terms of their travelled distances in a specified unit of time and their preferential positioning within the antenna network. To do so, the controllers worked in parallel to send the antenna data to a computer via a USB connection. The tracking accuracy of the system was evaluated by concurrently recording the animals’ behaviour with automated video imaging. During the two experiments, each lasting approximately one week, two different groups of three animals each showed a variable burrow occupancy and a nocturnal displacement under a standard photoperiod regime (12 h light:12 h dark), measured using the RFID method. Similar results were obtained with the video imaging. Our implemented RFID system was therefore capable of efficiently tracking the tested organisms and has a good potential for use on a wide variety of other marine organisms of commercial, aquaculture, and ecological interest. Full article
(This article belongs to the Section Physical Sensors)
Open AccessArticle The New Seafloor Observatory (OBSEA) for Remote and Long-Term Coastal Ecosystem Monitoring
Sensors 2011, 11(6), 5850-5872; doi:10.3390/s110605850
Received: 8 April 2011 / Revised: 25 May 2011 / Accepted: 30 May 2011 / Published: 31 May 2011
Cited by 39 | Viewed by 5444 | PDF Full-text (1434 KB) | HTML Full-text | XML Full-text
Abstract
A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring
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A suitable sampling technology to identify species and to estimate population dynamics based on individual counts at different temporal levels in relation to habitat variations is increasingly important for fishery management and biodiversity studies. In the past two decades, as interest in exploring the oceans for valuable resources and in protecting these resources from overexploitation have grown, the number of cabled (permanent) submarine multiparametric platforms with video stations has increased. Prior to the development of seafloor observatories, the majority of autonomous stations were battery powered and stored data locally. The recently installed low-cost, multiparametric, expandable, cabled coastal Seafloor Observatory (OBSEA), located 4 km off of Vilanova i la Gertrú, Barcelona, at a depth of 20 m, is directly connected to a ground station by a telecommunication cable; thus, it is not affected by the limitations associated with previous observation technologies. OBSEA is part of the European Multidisciplinary Seafloor Observatory (EMSO) infrastructure, and its activities are included among the Network of Excellence of the European Seas Observatory NETwork (ESONET). OBSEA enables remote, long-term, and continuous surveys of the local ecosystem by acquiring synchronous multiparametric habitat data and bio-data with the following sensors: Conductivity-Temperature-Depth (CTD) sensors for salinity, temperature, and pressure; Acoustic Doppler Current Profilers (ADCP) for current speed and direction, including a turbidity meter and a fluorometer (for the determination of chlorophyll concentration); a hydrophone; a seismometer; and finally, a video camera for automated image analysis in relation to species classification and tracking. Images can be monitored in real time, and all data can be stored for future studies. In this article, the various components of OBSEA are described, including its hardware (the sensors and the network of marine and land nodes), software (data acquisition, transmission, processing, and storage), and multiparametric measurement (habitat and bio-data time series) capabilities. A one-month multiparametric survey of habitat parameters was conducted during 2009 and 2010 to demonstrate these functions. An automated video image analysis protocol was also developed for fish counting in the water column, a method that can be used with cabled coastal observatories working with still images. Finally, bio-data time series were coupled with data from other oceanographic sensors to demonstrate the utility of OBSEA in studies of ecosystem dynamics. Full article
(This article belongs to the Section Remote Sensors)
Open AccessArticle A Novel Morphometry-Based Protocol of Automated Video-Image Analysis for Species Recognition and Activity Rhythms Monitoring in Deep-Sea Fauna
Sensors 2009, 9(11), 8438-8455; doi:10.3390/s91108438
Received: 25 August 2009 / Revised: 1 October 2009 / Accepted: 13 October 2009 / Published: 26 October 2009
Cited by 26 | Viewed by 10520 | PDF Full-text (2029 KB) | HTML Full-text | XML Full-text
Abstract
The understanding of ecosystem dynamics in deep-sea areas is to date limited by technical constraints on sampling repetition. We have elaborated a morphometry-based protocol for automated video-image analysis where animal movement tracking (by frame subtraction) is accompanied by species identification from animals’ outlines
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The understanding of ecosystem dynamics in deep-sea areas is to date limited by technical constraints on sampling repetition. We have elaborated a morphometry-based protocol for automated video-image analysis where animal movement tracking (by frame subtraction) is accompanied by species identification from animals’ outlines by Fourier Descriptors and Standard K-Nearest Neighbours methods. One-week footage from a permanent video-station located at 1,100 m depth in Sagami Bay (Central Japan) was analysed. Out of 150,000 frames (1 per 4 s), a subset of 10.000 was analyzed by a trained operator to increase the efficiency of the automated procedure. Error estimation of the automated and trained operator procedure was computed as a measure of protocol performance. Three displacing species were identified as the most recurrent: Zoarcid fishes (eelpouts), red crabs (Paralomis multispina), and snails (Buccinum soyomaruae). Species identification with KNN thresholding produced better results in automated motion detection. Results were discussed assuming that the technological bottleneck is to date deeply conditioning the exploration of the deep-sea. Full article
(This article belongs to the Special Issue Image Sensors 2009)

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