Spatiotemporal pattern analysis of potential light seine fishing areas in the East China sea using VIIRS day/night band imagery

Light seine fishing, one of the most efficient methods used in modern fisheries, is performed based on fish phototaxis. In this study, the East China Sea was selected as the study area, and fishing vessel pixels (pixels representing light seine fishing vessels) were detected in five years of Visible Infrared Imaging Radiometer Suite (VIIRS) day/night band (DNB) imagery according to three indicators: the Spike Median Index (SMI), Sharpness Index (SI), and Spike Height Index (SHI). Subsequently, cluster, barycenter, range and direction, and density analyses were conducted to comprehensively evaluate the spatiotemporal patterns of potential light seine fishing areas in the East China Sea. The following conclusions were drawn from the study: (1) the number of fishing vessel pixels exhibited obvious monthly characteristics that are consistent with the fishing moratorium that has been enforced in this region; (2) at the study area scale, light seine fishing occurred in one cluster, and the pattern in the interior of the cluster exhibited spatiotemporal periodicity; (3) the barycenter of the fishing areas displayed opposing movement trends in the first half and the second half of the year, and the movements were closely linked to water temperature changes. In addition, seasonally concentrated fishing areas were observed in winter, spring and summer; (4) the peak fishing month advanced from September to August beginning in 2014, and the fishing areas displayed a strong tendency in orientation that was highly consistent with the distribution of the Kuroshio Front in the East China Sea; and (5) light seine fishing activities were mainly concentrated in the second half of the year, especially in summer, but the intensity has declined in recent years. Our results are in good agreement with the results of other scholars and provide reliable information concerning where and when light seine fishing occurs. These results also suggest that VIIRS DNB imagery can be effectively used to detect light seine fishing areas.     

Perspective taking and synchronous argumentation for learning the day/night cycle

Changing practices in schools is a very complex endeavor. This paper is about new practices we prompted to foster collaboration and critical reasoning in science classrooms: the presentation of pictures representing different perspectives, small group synchronous argumentation, and moderation of synchronous argumentation. A CSCL tool helped in supporting synchronous argumentation through graphical representations of argumentative moves. We checked the viability of these practices in science classrooms. To do so, we investigated whether these practices led to conceptual learning, and undertook interactional analyses to study the behaviors of students and teachers. Thirty-two Grade 8 students participated in a series of activities on the day/night cycle. Learning was measured by the correctness of knowledge, the extent to which it was elaborated, the mental models that emerged from the explanations, the knowledge integration in explanations, and their simplicity. We showed that participants could learn the day/night cycle concept, as all measures of learning improved. For some students, it even led to conceptual change. However, the specific help provided by teachers during collective argumentation did not yield additional learning. The analysis of protocols of teacher-led collective argumentation indicated that although the teachers’ help was needed, some teachers had difficulties monitoring these synchronous discussions. We conclude that the next step of the design-research cycle should be devoted to (a) the development of new tools directed at helping teachers facilitate synchronous collective argumentation, and to (b) activities including teachers, designers, and researchers for elaborating new strategies to use these tools to improve the already positive learning outcomes from synchronous argumentation.     

Differences in day and night shift clinical performance in anesthesiology

OBJECTIVE: This study examined whether anesthesia residents (physicians in training) performed clinical duties in the operating room differently during the day versus at night. BACKGROUND: Fatigue from sleep deprivation and working through the night is common for physicians, particularly during residency training. METHODS: Using a repeated-measures design, we studied 13 pairs of day-night matched anesthesia cases. Dependent measures included task times, workload ratings, response to an alarm light latency task, and mood. RESULTS: Residents spent significantly less time on manual tasks and more time on monitoring tasks during the maintenance phase at night than during the day. Residents reported more negative mood at night than during the day, both pre- and postoperation. However, time of day had no effect on the mood change between pre- and postoperation. Workload ratings and the response time to an alarm light latency task were not significantly different between night and day cases. CONCLUSIONS: Because night shift residents had been awake and working for more than 16 hr, the observed differences in task performance and mood may be attributed to fatigue. The changes in task distribution during night shift work may represent compensatory strategies to maintain patient care quality while keeping perceived workload at a manageable level. APPLICATIONS: Fatigue effects during night shifts should be considered when designing work-rest schedules for clinicians. This matched-case control scheme can also be applied to study other phenomena associated with patient safety in the actual clinical environment.     

Qualitative changes in recall memory during day and night shifts

The effect of time of day on recall of words and drawings was studied in 29 French shiftworkers. Tests were carried out at 18:00, 22:00, 02:00 and 06:00. The task involved memorizing a list of 18 drawings for one half of the group, and 18 words (designating the corresponding figures) for the other half. At each time of day, the lists were presented both with and without an interpolated task. In the interpolated task condition, the first 9 items were followed by an interpolated imagery task and the last 9 by a spelling task, or vice versa. The results indicated an overall effect of time of day on the recall test, especially when memorizing drawings. At 18:00 in both the control and the interference condition, subjects recalled more words and drawings from the beginning of the list. Conversely, at 02:00, subjects recalled more words and drawings from the end of the list. The time spent in the interpolated comparison task varied with the time of day and was longer when memorizing drawings. The same time of day pattern of performance was found for spelling times. The implications upon issues concerning shiftwork and job demands are also discussed.     

Multiple cameras audio visual speech recognition using active appearance model visual features in car environment

Consideration of visual speech features along with traditional acoustic features have shown decent performance in uncontrolled auditory environment. However, most of the existing audio-visual speech recognition (AVSR) systems have been developed in the laboratory conditions and rarely addressed the visual domain problems. This paper presents an active appearance model (AAM) based multiple-camera AVSR experiment. The shape and appearance information are extracted from jaw and lip region to enhance the performance in vehicle environments. At first, a series of visual speech recognition (VSR) experiments are carried out to study the impact of each camera on multi-stream VSR. Four cameras in car audio-visual corpus is used to perform the experiments. The individual camera stream is fused to have four-stream synchronous hidden Markov model visual speech recognizer. Finally, optimum four-stream VSR is combined with single stream acoustic HMM to build five-stream AVSR. The dual modality AVSR system shows more robustness compared to acoustic speech recognizer across all driving conditions.     

Mapping geographical concentrations of economic activities in Europe using light at night (LAN) satellite data

Data on geographical concentrations of economic activities, such as manufacturing, construction, wholesale and retail trade, financial services, etc., are important for identifying clusters of economic activities (EAs) and concentrations of forces behind them. However, such data are essentially sparse due to limited reporting by individual countries and administrative entities. For example, at present, Eurostat provides EA data for <50% of all regional subdivisions of the third tier of the Nomenclature of Territorial Units for Statistics (NUTS3). Measurements of light at night (LAN), as captured by satellite sensors, are likely to differ in intensity, depending on the source. As a result, LAN levels can become a marker for EAs; the present study attempts to verify this possibility. As the present analysis indicates, the inclusion of LAN intensities in multivariate models (in addition to standard economic and locational variables) helps to explain up to 88.8% of the EA variation, performing especially well for manufacturing, construction, and agriculture (the adjusted coefficient of determination (R²-adjusted) is in the range of 0.754–0.888). The study thus confirms the feasibility of using LAN satellite measurements for reconstructing geographical patterns of EAs, information that may be restricted or is unavailable due to sparse or incomplete reporting.     

Physical workload,trapezius muscle activity,and neck pain in nurses' night and day shifts: A physiological evaluation

The purpose of this study was to compare physical workload, electromyography (EMG) of the trapezius muscle, neck pain and mental well-being at work between night and day shifts in twenty Swiss nurses. Work pulse (average increase of heart rate over resting heart rate) was lower during night (27 bpm) compared to day shifts (34 bpm; p < 0.01). Relative arm acceleration also indicated less physical activity during night (82% of average) compared to day shifts (110%; p < 0.01). Rest periods were significantly longer during night shifts. Trapezius muscle rest time was longer during night (13% of shift duration) than day shifts (7%; p < 0.01) and the 50th percentile of EMG activity was smaller (p = 0.02), indicating more opportunities for muscle relaxation during night shifts. Neck pain and mental well-being at work were similar between shifts. Subjective perception of burden was similar between shifts despite less physical burden at night, suggesting there are other contributing factors.     

Study of pre-storm environment by using rawinsonde and satellite observations

Abstract

Four groups of severe storms with a total outbreak of 27 tornadoes have been studied by using satellite remote sensing and rawinsonde observations. Geographical distributions of the areas of high moisture concentration at 850 mb height, 7 to 12 hours prior to the formation of the storms, using the best available conventional rawinsonde soundings, and 2 to 3 hours prior to the touchdown of tornadoes, using the three hourly AVE-SESAME soundings, were analysed in conjunction with the ambient pre-storm wind and air mass stability. Using the area of high moisture concentration as a basis, the time-dependent geographical variation of the tropopause height distribution was analysed. It was found that, within the area of a low-level high concentration of moisture, the local tropopause height was lowest at the time of the storm cloud formation and development. The potential energy storage per unit area for the overshooting clouds penetrating above the tropopause is closely related to the intensity of the storms produced, in terms of the Fujita scale of storm damage. To make up the discrepancy of more than 3-hour intervals of available sounding data, numerical cloud modelling is carried out. The results obtained from the cloud modelling are in agreement with the results of satellite remote sensing and rawinsonde observations drawn earlier.     

Biomass retrieval from high-dimensional active/passive remote sensing data by using artificial neural networks

Retrieval of the biomass parameters from active/passive microwave remote sensing data is performed based on an iterative inversion of the artificial neural network (ANN). The ANN is trained by a set of the measurements of active and passive remote sensing and the ground truth data versus Day of Year during growth. Once the ANN training is complete, the ANN can be used to retrieve the temporal variations of the biomass parameters from another set of observation data. The retrieved biomass include canopy height, canopy water content and dry matter fraction, and the wetness of the underlying land. Two examples for wheat and oat are illustrated. The retrieved biomass parameters agree well with the real data of the ground truth.     

Detection of river/sea ice deformation using satellite interferometry: limits and potential

In this paper, we present a study consisting of the application of radar interferometry for river/sea ice monitoring in inhabited regions and on commercial waterways. The sites studied are located in Canadian regions where ice jams constitute a common winter hazard that can cause extensive socio-economic damage and impose severe restrictions on ship traffic. ERS and Radarsat images were jointly used with traditional in situ observations to detect ice break-up in order to prevent ice jams and related problems. A coherence study served to define the synthetic aperture radar interferometry (InSAR) limits for river/sea ice dynamics monitoring. Other factors that also help to define the limits of InSAR technology for this application include the frequency of image acquisition, the minimum dimension of detected ice floes and the determination of appropriate ice types. Significant phase shifts were found for small ice floes of several hundred metres with ERS-tandem images. The analysis of the interferograms showed that it is possible to detect deformations in the ice shelf and to discriminate quantitatively the horizontal and vertical components of ice movement when the interferograms are combined with traditional observations such as meteorological data, water level, water flow and ice charts. The deformation estimated on a piece of fast river ice can be interpreted as the first sign of the ice break-up. On an estuary river that is a busy seaway, a qualitative interpretation of the interferograms served to highlight the interaction of river and tidal flows affecting the ice cover. We showed, in particular, the potential of radar interferometry and its integration with other techniques to help the authorities to prevent problems related to ice jams.     

Determination of sea surface temperature at large observation angles using an angular and emissivity-dependent split-window equation

This paper proposes an angular and emissivity-dependent split-window equation that permits the determination of the sea surface temperature (SST) to a reasonable level of accuracy for any observation angle, including large viewing angles at the image edges of satellite sensors with wide swaths. This is the case of the MODIS radiometer both on EOS Terra/Aqua platforms, with observation angles of up to 65° at the surface, for which the split-window equation has been developed in this study. The algorithm takes into account the angular dependence of both the atmospheric correction (due to the increase of the atmospheric optical path with angle) and the emissivity correction (since sea surface emissivity (SSE) decreases with observation angle). Angular-dependent coefficients have been estimated for the atmospheric terms, and also an explicit dependence on the SSE has been included in the algorithm, as this parameter has values different to a blackbody surface for off-nadir angles, the SSEs also being dependent on surface wind speed. The proposed algorithm requires as input data at-sensor brightness temperatures for the split-window bands (31 and 32 of MODIS), the observation angle at each pixel, an estimate of the water vapor content (which is provided by the MODIS MOD07/MYD07 products) and accurate SSE values for both channels. The preliminary results show a good agreement between SSTs estimated by the proposed equation for off-nadir viewings of MODIS-Terra images and in situ SST measurements, with a root-mean square error (RMSE) of about ± 0.3 K, for which the MODIS SST product gives an RMSE larger than ± 0.7 K.     

Training and learning for crisis management using a virtual simulation/gaming environment

Recent advances in computers, networking, and telecommunications offer new opportunities for using simulation and gaming as methodological tools for improving crisis management. It has become easy to develop virtual environments to support games, to have players at distributed workstations interacting with each other, to have automated controllers supply exogenous events to the players, to enable players to query online data files during the game, and to prepare presentation graphics for use during the game and for post-game debriefings. Videos can be used to present scenario updates to players in “newscast” format and to present pre-taped briefings by experts to players. Organizations responsible for crisis management are already using such technologies in constructing crisis management systems (CMSs) to coordinate response to a crisis, provide decision support during a crisis, and support activities prior to the crisis and after the crisis. If designed with gaming in mind, those same CMSs could be easily used in a simulation mode to play a crisis management game. Such a use of the system would also provide personnel with opportunities to rehearse for real crises using the same tools they would have available to them in a real crisis. In this paper, we provide some background for the use of simulation and gaming in crisis management training, describe an architecture for simulation and gaming, and present a case study to illustrate how virtual environments can be used for crisis management training.     

Fast and automatic city-scale environment modelling using hard and/or weak constrained bundle adjustments

To provide high-quality augmented reality service in a car navigation system, accurate 6 degrees of freedom (DoF) localization is required. To ensure such accuracy, most current vision-based solutions rely on an off-line large-scale modelling of the environment. Nevertheless, while existing solutions to model the environment require expensive equipments and/or a prohibitive computation time, we propose in this paper a complete framework that automatically builds an accurate large-scale database of landmarks using only a standard camera, a low-cost global positioning system (GPS) and a geographic information system (GIS). As illustrated in the experiments, only few minutes are required to model large-scale environments. The resulting databases can then be used by an on-line localization algorithm to ensure high-quality augmented reality experiences.     

Speeding up algorithm selection using average ranking and active testing by introducing runtime

Algorithm selection methods can be speeded-up substantially by incorporating multi-objective measures that give preference to algorithms that are both promising and fast to evaluate. In this paper, we introduce such a measure, A3R, and incorporate it into two algorithm selection techniques: average ranking and active testing. Average ranking combines algorithm rankings observed on prior datasets to identify the best algorithms for a new dataset. The aim of the second method is to iteratively select algorithms to be tested on the new dataset, learning from each new evaluation to intelligently select the next best candidate. We show how both methods can be upgraded to incorporate a multi-objective measure A3R that combines accuracy and runtime. It is necessary to establish the correct balance between accuracy and runtime, as otherwise time will be wasted by conducting less informative tests. The correct balance can be set by an appropriate parameter setting within function A3R that trades off accuracy and runtime. Our results demonstrate that the upgraded versions of Average Ranking and Active Testing lead to much better mean interval loss values than their accuracy-based counterparts.     

Assessing the potential of SeaWiFS and MODIS for estimating chlorophyll concentration in turbid productive waters using red and near-infrared bands

Bio-optical algorithms for remote estimation of chlorophyll-a concentration (Chl) in case-1 waters exploit the upwelling radiation in the blue and green spectral regions. In turbid productive waters other constituents, that vary independently of Chl, absorb and scatter light in these spectral regions. As a consequence, the accurate estimation of Chl in turbid productive waters has so far not been feasible from satellite sensors. The main purpose of this study was to evaluate the extent to which near-infrared (NIR) to red reflectance ratios could be applied to the Sea Wide Field-of-View Sensor (SeaWiFS) and the Moderate Imaging Spectrometer (MODIS) to estimate Chl in productive turbid waters. To achieve this objective, remote-sensing reflectance spectra and relevant water constituents were collected in 251 stations over lakes and reservoirs with a wide variability in optical parameters (i.e. 4 ≤ Chl ≤ 240 mg m^− 3; 18 ≤ Secchi disk depth ≤ 308 cm). SeaWiFS and MODIS NIR and red reflectances were simulated by using the in-situ hyperspectral data. The proposed algorithms predicted Chl with a relative random uncertainty of approximately 28% (average bias between − 1% and − 4%). The effects of reflectance uncertainties on the predicted Chl were also analyzed. It was found that, for realistic ranges of R_rs uncertainties, Chl could be estimated with a precision better than 40% and an accuracy better than ± 35%. These findings imply that, provided that an atmospheric correction scheme specific for the red-NIR spectral region is available, the extensive database of SeaWiFS and MODIS images could be used to quantitatively monitor Chl in turbid productive waters.     

Error recovery in the assembly of a Self-Organizing Manipulator by using active visual and force sensing

This paper deals with the assembly of aSelf-OrganizingManipulator (SOM) by using the method ofActive Sensing. We set a 6-axis force/torque sensor in the wrist of a manipulator and a CCD camera in the hand of another manipulator. By cooperation of hand and eye, human beings can do a variety of versatile work. The eyes guide the motion of the hand, while the hand moves to make the object easy to see. We try to construct a system working in the same way as a human being. We integrate a vision system, a manipulator, and a force/torque sensor into a hand-eye working system. The scene simplification is based on the controlled motion of camera and manipulator. A method of theAverage Visible Ratio (AVR) is proposed to evaluate the viewpoint of the movable camera. A strategy for planning the assembly is presented. The efficiency of the system is illustrated by experiments.     

Discrimination of growth and water stress in wheat by various vegetation indices through clear and turbid atmospheres

Reflectance data were obtained over a drought-stressed and a well-watered wheat plot with a hand-held radiometer having bands similar to the MSS bands of the Landsat satellites. Data for 48 clear days were interpolated to yield reflectance values for each day of the growing season, from planting until harvest. With an atmospheric path radiance model and Landsat 2 calibration data, the reflectances were used to simulate Landsat digital counts (not quantized) for the four Landsat bands for each day of the growing season, through a clear ($\text{?100-}\text{km}$ meteorological range) and a turbid ($\text{?10-}\text{km}$ meteorological range) atmosphere. Several ratios and linear combinations of bands were calculated using the simulated data, then assessed for their relative ability to discriminate vegetative growth and plant stress through the two atmospheres. The results showed that water stress was not detected by any of the indices until after growth was retarded, and the sensitivity of the various indices to vegetation depended on plant growth stage and atmospheric path radiance.     

Structuring group decision making in a web-based environment by using the nominal group technique

The Nominal Group Technique (NGT) is a structured decision-making technique widely used both in industry and academia as a tool to aid in planning and decision-making processes. The main goal of this study was to evaluate the performance of NGT in a web-based environment compared to its traditional counterpart. Comparisons were made along several performance and process-related dimensions. First, the decision process and experimental methodology are introduced. Second, the interface design used during the online sessions is described. Next, the response variables were explored following two difference approaches. The first approach compared the response variables from the traditional and the online setting. The second approach assessed the differences in perceived values before and after the session was conducted. Results revealed that the traditional NGT outperformed the online version in the variables related to the process. However, traditional groups did not significantly differ from online groups with respect to the variables related to the outcomes. Finally, we suggest conditions for enhanced productivity in idea-generating and problem-solving groups by providing some sustaining evidence.     

Comprehensive modelling and simulation of cylindrical nanoparticles manipulation by using a virtual reality environment

With the expansion of nanotechnology, robots based on atomic force microscope (AFM) have been widely used as effective tools for displacing nanoparticles and constructing nanostructures. One of the most limiting factors in AFM-based manipulation procedures is the inability of simultaneously observing the controlled pushing and displacing of nanoparticles while performing the operation. To deal with this limitation, a virtual reality environment has been used in this paper for observing the manipulation operation. In the simulations performed in this paper, first, the images acquired by the atomic force microscope have been processed and the positions and dimensions of nanoparticles have been determined. Then, by dynamically modelling the transfer of nanoparticles and simulating the critical force-time diagrams, a controlled displacement of nanoparticles has been accomplished. The simulations have been further developed for the use of rectangular, V-shape and dagger-shape cantilevers. The established virtual reality environment has made it possible to simulate the manipulation of biological particles in a liquid medium.