946 resultados para behavioral tracking


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The courtship behavior of the navel orangeworm, Amyelois transitella, was examined in a wind tunnel. Sixty nine courtship sequences were analyzed and successful sequences divided into two categories: rapid courtship sequences, which involved few breaks in contact, short or no periods of male/female chasing and lasted <10 s between initial contact and mating; and prolonged courtship sequences, which involved many breaks in contact, extended periods of male/female chasing and lasted >10 s. Fifty six (81%) courtships were successful (50.7% rapid courtship and 30.4% prolonged courtship); the remaining 13 (18.8%) sequences were failed courtships. Of failed courtships, 9 (13.0%) were due to males losing contact with females during courtship chases and 4 (5.8%) due to females flying away immediately after male contact. Of all courtship sequences involving a break in contact during a chase, 38.5% resulted in an unsuccessful mating attempt. These findings contrast with previous studies of the courtship behavior of the navel orangeworm, potentially indicating that the type of bioassay used to study courtship may have a large effect on the behavioral sequences displayed. We evaluate several diagnostic techniques for the analysis of sequences of behavioral transitions.

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Traditionally, biosensors have been defined as consisting of two parts; a biological part, which is used to detect chemical or physical changes in the environment, and a corresponding electronic component, which tranduces the signal into an electronically readable format. Biosensors are used for detection of volatile compounds often at a level of sensitivity unattainable by traditional analytical techniques. Classical biosensors and traditional analytical techniques do not allow an ecological context to be imparted to the volatile compound/s under investigation. Therefore, we propose the use of behavioral biosensors, in which a whole organism is utilized for the analysis of chemical stimuli. In this case, the organism detects a chemical or physical change and demonstrates this detection through modifications of its behavior; it is the organism's behavior itself that defines the biosensor. In this review, we evaluate the use and future prospects of behavioral biosensors, with a particular focus on parasitic wasps.

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This paper presents the mathematical development of a body-centric nonlinear dynamic model of a quadrotor UAV that is suitable for the development of biologically inspired navigation strategies. Analytical approximations are used to find an initial guess of the parameters of the nonlinear model, then parameter estimation methods are used to refine the model parameters using the data obtained from onboard sensors during flight. Due to the unstable nature of the quadrotor model, the identification process is performed with the system in closed-loop control of attitude angles. The obtained model parameters are validated using real unseen experimental data. Based on the identified model, a Linear-Quadratic (LQ) optimal tracker is designed to stabilize the quadrotor and facilitate its translational control by tracking body accelerations. The LQ tracker is tested on an experimental quadrotor UAV and the obtained results are a further means to validate the quality of the estimated model. The unique formulation of the control problem in the body frame makes the controller better suited for bio-inspired navigation and guidance strategies than conventional attitude or position based control systems that can be found in the existing literature.

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The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the ‘THORPEX Interactive Grand Global Ensemble’ (TIGGE) offers a new opportunity for the development of state-of-the-art early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km2) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.

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Imitation is an important form of social behavior, and research has aimed to discover and explain the neural and kinematic aspects of imitation. However, much of this research has featured single participants imitating in response to pre-recorded video stimuli. This is in spite of findings that show reduced neural activation to video vs. real life movement stimuli, particularly in the motor cortex. We investigated the degree to which video stimuli may affect the imitation process using a novel motion tracking paradigm with high spatial and temporal resolution. We recorded 14 positions on the hands, arms, and heads of two individuals in an imitation experiment. One individual freely moved within given parameters (moving balls across a series of pegs) and a second participant imitated. This task was performed with either simple (one ball) or complex (three balls) movement difficulty, and either face-to-face or via a live video projection. After an exploratory analysis, three dependent variables were chosen for examination: 3D grip position, joint angles in the arm, and grip aperture. A cross-correlation and multivariate analysis revealed that object-directed imitation task accuracy (as represented by grip position) was reduced in video compared to face-to-face feedback, and in complex compared to simple difficulty. This was most prevalent in the left-right and forward-back motions, relevant to the imitator sitting face-to-face with the actor or with a live projected video of the same actor. The results suggest that for tasks which require object-directed imitation, video stimuli may not be an ecologically valid way to present task materials. However, no similar effects were found in the joint angle and grip aperture variables, suggesting that there are limits to the influence of video stimuli on imitation. The implications of these results are discussed with regards to previous findings, and with suggestions for future experimentation.

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Verbal communication is essential for human society and human civilization. Non-verbal communication, on the other hand, is more widely used not only by human but also other kind of animals, and the content of information is estimated even larger than the verbal communication. Among the non-verbal communication mutual motion is the simplest and easiest to study experimentally and analytically. We measured the power spectrum of the hand velocity in various conditions and clarified the following points on the feed-back and feed- forward mechanism as basic knowledge to understand the condition of good communication.

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In the present study, to shed light on a role of positional error correction mechanism and prediction mechanism in the proactive control discovered earlier, we carried out a visual tracking experiment, in which the region where target was shown, was regulated in a circular orbit. Main results found in this research were following. Recognition of a time step, obtained from the environmental stimuli, is required for the predictive function. The period of the rhythm in the brain obtained from environmental stimuli is shortened about 10%, when the visual information is cut-off. The shortening of the period of the rhythm in the brain accelerates the motion as soon as the visual information is cut-off, and lets the hand motion precedes the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand precedes in average the target when the predictive mechanism dominates the error-corrective mechanism.

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The Solar Stormwatch team reviews progress and prospects for this highly effective citizen-science project focused on the Sun.

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This paper describes a new approach to detect and track maritime objects in real time. The approach particularly addresses the highly dynamic maritime environment, panning cameras, target scale changes, and operates on both visible and thermal imagery. Object detection is based on agglomerative clustering of temporally stable features. Object extents are first determined based on persistence of detected features and their relative separation and motion attributes. An explicit cluster merging and splitting process handles object creation and separation. Stable object clus- ters are tracked frame-to-frame. The effectiveness of the approach is demonstrated on four challenging real-world public datasets.

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This paper presents a quantitative evaluation of a tracking system on PETS 2015 Challenge datasets using well-established performance measures. Using the existing tools, the tracking system implements an end-to-end pipeline that include object detection, tracking and post- processing stages. The evaluation results are presented on the provided sequences of both ARENA and P5 datasets of PETS 2015 Challenge. The results show an encouraging performance of the tracker in terms of accuracy but a greater tendency of being prone to cardinality error and ID changes on both datasets. Moreover, the analysis show a better performance of the tracker on visible imagery than on thermal imagery.

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Farmers are necessary agents in global efforts to conserve the environment now that croplands and pastures together constitute the largest terrestrial system on Earth – covering some 48% of ice-free land surface. Whereas standard economic models predict that farmers will participate in conservation programs so long as they are profitable, empirical findings from behavioral economics point to a number of normally unobservable preferences that may influence the decision-making process. This study tests, for the first time, whether heterogeneity in behavioral preferences correlates with decisions to participate in Payments for Environmental Services (PES) programs. We elicit individual trust and time preferences using economic experiments and link resulting measures to household survey data and participation decisions in a Ugandan PES program. We find that farmers who exhibit a preference for proximate gains – present-biased preferences – are 47.7% more likely to participate in the program than those who show time-consistent or future-biased preferences. This result has implications for ongoing and planned PES programs involving farmers, particularly in Africa, by highlighting a potential relationship between payment timing and participation, and further validates the use of behavioral experiments in explaining real-world decisions.

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The use of economic incentives for biodiversity (mostly Compensation and Reward for Environmental Services including Payment for ES) has been widely supported in the past decades and became the main innovative policy tools for biodiversity conservation worldwide. These policy tools are often based on the insight that rational actors perfectly weigh the costs and benefits of adopting certain behaviors and well-crafted economic incentives and disincentives will lead to socially desirable development scenarios. This rationalist mode of thought has provided interesting insights and results, but it also misestimates the context by which ‘real individuals’ come to decisions, and the multitude of factors influencing development sequences. In this study, our goal is to examine how these policies can take advantage of some unintended behavioral reactions that might in return impact, either positively or negatively, general policy performances. We test the effect of income's origin (‘Low effort’ based money vs. ‘High effort’ based money) on spending decisions (Necessity vs. Superior goods) and subsequent pro social preferences (Future pro-environmental behavior) within Madagascar rural areas, using a natural field experiment. Our results show that money obtained under low effort leads to different consumption patterns than money obtained under high efforts: superior goods are more salient in the case of low effort money. In parallel, money obtained under low effort leads to subsequent higher pro social behavior. Compensation and rewards policies for ecosystem services may mobilize knowledge on behavioral biases to improve their design and foster positive spillovers on their development goals.

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Clustering methods are increasingly being applied to residential smart meter data, providing a number of important opportunities for distribution network operators (DNOs) to manage and plan the low voltage networks. Clustering has a number of potential advantages for DNOs including, identifying suitable candidates for demand response and improving energy profile modelling. However, due to the high stochasticity and irregularity of household level demand, detailed analytics are required to define appropriate attributes to cluster. In this paper we present in-depth analysis of customer smart meter data to better understand peak demand and major sources of variability in their behaviour. We find four key time periods in which the data should be analysed and use this to form relevant attributes for our clustering. We present a finite mixture model based clustering where we discover 10 distinct behaviour groups describing customers based on their demand and their variability. Finally, using an existing bootstrapping technique we show that the clustering is reliable. To the authors knowledge this is the first time in the power systems literature that the sample robustness of the clustering has been tested.

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Understanding how wildlife responds to road and traffic is essential for effective conservation. Yet, not many studies have evaluated how roads influence wildlife in protected areas, particularly within the large iconic African National Parks where tourism is mainly based on sightings from motorized vehicles with the consequent development and intense use of roads. To reduce this knowledge gap, we studied the behavioral response and local spatial distribution of impala Aepyceros melampus along the heterogeneous (with variation in road surface type and traffic intensity) road-network of Kruger National Park (KNP, South Africa). We surveyed different types of roads (paved and unpaved) recording the occurrence of flight responses among sighted impala and describing their local spatial distribution (in relation to the roads). We observed relatively few flight responses (19.5% of 118 observations), suggesting impalas could be partly habituated to vehicles in KNP. In addition, impala local distribution is apparently unaffected by unpaved roads, yet animals seem to avoid the close proximity of paved roads. Overall, our results suggest a negative, albeit small, effect of traffic intensity, and of presence of pavement on roads on the behavior of impala at KNP. Future studies would be necessary to understand how roads influence other species, but our results show that even within a protected area that has been well-visited for a long time, wildlife can still be affected by roads and traffic. This result has ecological (e.g., changes in spatial distribution of fauna) and management implications (e.g., challenges of facilitating wildlife sightings while minimizing disturbance) for protected areas where touristic activities are largely based on driving.