134 research outputs found

    Animating Predator and Prey Fish Interactions

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    Schooling behavior is one of the most salient social and group activities among fish. They form schools for social reasons like foraging, mating and escaping from predators. Animating a school of fish is difficult because they are large in number, often swim in distinctive patterns that is they take the shape of long thin lines, squares, ovals or amoeboid and exhibit complex coordinated patterns especially when they are attacked by a predator. Previous work in computer graphics has not provided satisfactory models to simulate the many distinctive interactions between a school of prey fish and their predator, how does a predator pick its target? and how does a school of fish react to such attacks? This dissertation presents a method to simulate interactions between prey fish and predator fish in the 3D world based on the biological research findings. Firstly, a model is described by representing a school of fish as a complex network information flow with structural properties. Using this model, a predator fish targeting isolated peripheral fish is simulated. Secondly, the escape behavior state machine model and escape maneuvers exhibited by fish schools are described. The escape maneuvers include compact, avoid, fast avoid, skitter, fountain, flash, ball, split, join, herd, vacuole, and hourglass are identified in the biological studies. This proposed escape behavior animation model can free an animator from dealing with the low-level animations but instead, control the fish behavior on a higher level by modifying a state machine and a small set of system parameters. With the state machine and relatively few system parameters, the proposed system is stable, predictable, and easy to tune, which represent important properties for animators to control the outcome. This system is developed in Unity (3D). In addition, a plug-in is also developed for full-fledged graphics tool Blender software to simulate escape maneuvers. The animator has to simply select escape maneuvers, adjust parameters and work on animating predator using keyframe method. It does not deal with the state machine model. The proposed model is useful not only in generating group behaviors but also in scientific visualization tool for studying fish behavior

    Evolution of swarming behavior is shaped by how predators attack

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    Animal grouping behaviors have been widely studied due to their implications for understanding social intelligence, collective cognition, and potential applications in engineering, artificial intelligence, and robotics. An important biological aspect of these studies is discerning which selection pressures favor the evolution of grouping behavior. In the past decade, researchers have begun using evolutionary computation to study the evolutionary effects of these selection pressures in predator-prey models. The selfish herd hypothesis states that concentrated groups arise because prey selfishly attempt to place their conspecifics between themselves and the predator, thus causing an endless cycle of movement toward the center of the group. Using an evolutionary model of a predator-prey system, we show that how predators attack is critical to the evolution of the selfish herd. Following this discovery, we show that density-dependent predation provides an abstraction of Hamilton's original formulation of ``domains of danger.'' Finally, we verify that density-dependent predation provides a sufficient selective advantage for prey to evolve the selfish herd in response to predation by coevolving predators. Thus, our work corroborates Hamilton's selfish herd hypothesis in a digital evolutionary model, refines the assumptions of the selfish herd hypothesis, and generalizes the domain of danger concept to density-dependent predation.Comment: 25 pages, 11 figures, 5 tables, including 2 Supplementary Figures. Version to appear in "Artificial Life

    The use of active sonar to study cetaceans

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    Cetacean species face serious challenges worldwide due to the increasing noise pollution brought to their environment by human activities such as seismic exploration. Regulation of these activities is vaguely defined and uncoordinated. Visual observations and passive listening devices, aimed at preventing conflicts between human wealth and cetaceans’ health have some fundamental limitations and may consequently fail their mitigation purposes. Active sonar technology could be the optimal solution to implement mitigation of such human activities. In my thesis, the proper sonar unit was used to test the feasibility to detect cetaceans in situ. Omnidirectional sonars could be the optimal solution to monitor the presence of cetaceans in the proximity of potential danger areas. To use this class of sonar in a quantitative manner, the first step was to develop a calibration method. This thesis links in situ measurements of target strength (TS) with variation trends linked to the behavior, morphology and physiology of cetacean. The butterfly effect of a cetacean’s body was described for a fin whale insonified from different angles. A relationship between whale respiration and TS energy peaks was tested through a simple prediction model which seems very promising for further implementation. The effect of lung compression on cetacean TS due to increasing depth was tested through a basic mathematical model. The model fit the in situ TS measurements. TS measurements at depth of a humpback whale, when post-processed, correspond to TS measurements recorded at the surface. Sonar technology is clearly capable of detecting whale foot prints around an operating vessel. Sonar frequency response shows that frequencies between 18 and 38 kHz should be employed. This work has established a baseline and raised new questions so that active sonar can be developed and employed in the best interest for the whales involved in potentially harmful conflicts with man

    Camouflage in a dynamic world

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    USING VIRTUAL REALITY TO INVESTIGATE ‘PROTEAN’ ANTI-PREDATOR BEHAVIOUR

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    Prey animals have evolved a wide variety of behaviours to combat the threat of predation, many of which have received considerable empirical and theoretical attention and are generally well understood in terms of their function and mechanistic underpinning. However, one of the most commonly observed and taxonomically widespread antipredator behaviours of all has, remarkably, received almost no experimental investigation: so-called ‘protean’ behaviour. This is defined as ‘behaviour that is sufficiently unpredictable to prevent a predator anticipating in detail the future position or actions of its prey’. In this thesis, I have elucidated the mechanisms that allow protean behaviour to be an effective anti-predatory response. This was explored with two approaches. Firstly, through the novel and extremely timely use of virtual reality to allow human ‘predators’ to attack and chase virtual prey in three-dimensions from a first-person perspective, thereby bringing the realism that has been missing from previous studies on predator-prey dynamics. Secondly through the three-dimensional tracking of protean behaviour in a highly tractable model species, the painted lady butterfly (Vanessa cardui). I explored this phenomenon in multiple contexts. Firstly, I simulated individual protean prey and explored the effects of unpredictability in their movement rules with respect to targeting accuracy of human ‘predators’ in virtual reality. Next, I examined the concept of ‘protean insurance’ via digitised movements of the painted lady butterfly, exploring the qualities of this animals’ movement paths related to human targeting ability. I then explored how the dynamics of animal groupings affected protean movement. Specifically, I investigated how increasing movement path complexity interacted with the well-documented ‘confusion effect’. I explored this question using both an experimental study and a VR citizen science game disseminated to the general public via the video game digital distribution service ‘Steam’. Subsequently, I explored another phenomenon associated with groupings of prey items; the ‘oddity effect’, which describes the preferential targeting of phenotypically odd individuals by predators. Typically, this phenomenon is associated with oddity of colouration or size. In this case, I investigated whether oddity of protean movement patterns relative to other group members could induce a ‘behavioural oddity effect’. Finally, I used a specialised genetic algorithm (GA) that was driven by human performance with respect to targeting prey items. I investigated the emergent protean movement paths that resulted from sustained predation pressure from humans. Specifically, I examined the qualities of the most fit movement paths with respect to control evolutions that were not under the selection pressure of human performance (randomised evolution). In the course of this thesis, I have gained a deeper understanding of a near ubiquitous component of predator prey interactions that has until recently been the subject of little empirical study. These findings provide important insights into the understudied phenomenon of protean movement, which are directly applicable to predator –prey dynamics within a broad range of taxa

    The Impact of Design-Based Modeling Instruction on Seventh Graders\u27 Spatial Abilities and Model-Based Argumentation

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    Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students\u27 spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal\u27s form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students\u27 arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed models to better assist them in scientific argumentation over paper drawing models. In fact, when given a choice, students rarely used paper drawing to assist in argument. There was also a difference in model utility between the two different model types. Participants explicitly used 3D printed models to complete gestural modeling, while participants rarely looked at 2D models when involved in gestural modeling. This study\u27s findings added to current theory dealing with the varied spatial challenges involved in different modes of expressed models. This study found that depth, symmetry and the manipulation of perspectives are typically spatial challenges students will attend to using CAD while they will typically ignore them when drawing using paper and pencil. This study also revealed a major difference in model-based argument in a design-based instruction context as opposed to model-based argument in a typical science classroom context. In the context of design-based instruction, data revealed that design process is an important part of model-based argument. Due to the importance of design process in model-based argumentation in this context, trusted methods of argument analysis, like the coding system of the IASCA, was found lacking in many respects. Limitations and recommendations for further research were also presented

    The Impact of Design-Based Modeling Instruction on Seventh Graders\u27 Spatial Abilities and Model-Based Argumentation

    Get PDF
    Due to the call of current science education reform for the integration of engineering practices within science classrooms, design-based instruction is receiving much attention in science education literature. Although some aspect of modeling is often included in well-known design-based instructional methods, it is not always a primary focus. The purpose of this study was to better understand how design-based instruction with an emphasis on scientific modeling might impact students\u27 spatial abilities and their model-based argumentation abilities. In the following mixed-method multiple case study, seven seventh grade students attending a secular private school in the Mid-Atlantic region of the United States underwent an instructional intervention involving design-based instruction, modeling and argumentation. Through the course of a lesson involving students in exploring the interrelatedness of the environment and an animal\u27s form and function, students created and used multiple forms of expressed models to assist them in model-based scientific argument. Pre/post data were collected through the use of The Purdue Spatial Visualization Test: Rotation, the Mental Rotation Test and interviews. Other data included a spatial activities survey, student artifacts in the form of models, notes, exit tickets, and video recordings of students throughout the intervention. Spatial abilities tests were analyzed using descriptive statistics while students\u27 arguments were analyzed using the Instrument for the Analysis of Scientific Curricular Arguments and a behavior protocol. Models were analyzed using content analysis and interviews and all other data were coded and analyzed for emergent themes. Findings in the area of spatial abilities included increases in spatial reasoning for six out of seven participants, and an immense difference in the spatial challenges encountered by students when using CAD software instead of paper drawings to create models. Students perceived 3D printed models to better assist them in scientific argumentation over paper drawing models. In fact, when given a choice, students rarely used paper drawing to assist in argument. There was also a difference in model utility between the two different model types. Participants explicitly used 3D printed models to complete gestural modeling, while participants rarely looked at 2D models when involved in gestural modeling. This study\u27s findings added to current theory dealing with the varied spatial challenges involved in different modes of expressed models. This study found that depth, symmetry and the manipulation of perspectives are typically spatial challenges students will attend to using CAD while they will typically ignore them when drawing using paper and pencil. This study also revealed a major difference in model-based argument in a design-based instruction context as opposed to model-based argument in a typical science classroom context. In the context of design-based instruction, data revealed that design process is an important part of model-based argument. Due to the importance of design process in model-based argumentation in this context, trusted methods of argument analysis, like the coding system of the IASCA, was found lacking in many respects. Limitations and recommendations for further research were also presented

    Categorical organization and machine perception of oscillatory motion patterns

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    Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Architecture, 2000.Includes bibliographical references (p. 126-132).Many animal behaviors consist of using special patterns of motion for communication, with certain types of movements appearing widely across animal species. Oscillatory motions in particular are quite prevalent, where many of these repetitive movements can be characterized by a simple sinusoidal model with very specific and limited parameter values. We develop a computational model of categorical perception of these motion patterns based on their inherent structural regularity. The model proposes the initial construction of a hierarchical ordering of the model parameters to partition them into sub-categorical specializations. This organization is then used to specify the types and layout of localized computations required for the corresponding visual recognition system. The goal here is to do away with ad hoc motion recognition methods of computer vision, and instead exploit the underlying structural description for a motion category as a motivating mechanism for recognition. We implement this framework and present an analysis of the approach with synthetic and real oscillatory motions, and demonstrate its applicability within an interactive artificial life environment. With this categorical foundation for the description and recognition of related motions, we gain insight into the basis and development of a machine vision system designed to recognize these patterns.by James W. Davis.Ph.D

    Book of Abstracts

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    ICES Annual Science Conference, 19 – 23 September 2011, Gdańsk Music and Congress Center, Gdańsk, Poland. IMR contributors: Benjamin Planque, Torild Johansen, Tuula Skarstein, Jon‐Ivar Westgaard, Halvor Knutsen, Kristin Helle, Michael Pennington, Marek Ostrowski, Nils Olav Handegard, Mette Skern‐Mauritzen, Edda Johannesen, Ulf Lindstrøm, Harald Gjøsæter, Ken Drinkwater, Trond Kristiansen, Geir Ottersen, Esben Moland Olse
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