Conferences related to Animal behavior

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2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)

The goal of the 14th ASME/IEEE MESA2018 is to bring together experts from the fields of mechatronic and embedded systems, disseminate the recent advances in the area, discuss future research directions, and exchange application experience. The main achievement of MESA2018 is to bring out and highlight the latest research results and developments in the IoT (Internet of Things) era in the field of mechatronics and embedded systems.


2018 7th IEEE International Conference on Biomedical Robotics and Biomechatronics (Biorob)

The RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics - BioRob 2018 - is a joint effort of the two IEEE Societies of Robotics and Automation - RAS - and Engineering in Medicine and Biology - EMBS.BioRob covers both theoretical and experimental challenges posed by the application of robotics and mechatronics in medicine and biology. The primary focus of Biorobotics is to analyze biological systems from a "biomechatronic" point of view, trying to understand the scientific and engineering principles underlying their extraordinary performance. This profound understanding of how biological systems work, behave and interact can be used for two main objectives: to guide the design and fabrication of novel, high performance bio-inspired machines and systems for many different applications; and to develop novel nano, micro-, macro- devices that can act upon, substitute parts of, and assist human beings in prevention, diagnosis, surgery, prosthetics, rehabilitation.


2017 10th International Symposium on Computational Intelligence and Design (ISCID)

Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models. The application of computational intelligence techniques into industrial design, interactive design, media design, and engineering design are also within the scope.

  • 2016 9th International Symposium on Computational Intelligence and Design (ISCID)

    Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models.

  • 2015 8th International Symposium on Computational Intelligence and Design (ISCID)

    Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation,Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems andother similar computational models.

  • 2014 7th International Symposium on Computational Intelligence and Design (ISCID)

    Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation,Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems andother similar computational models.

  • 2013 6th International Symposium on Computational Intelligence and Design (ISCID)

    Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models.

  • 2012 5th International Symposium on Computational Intelligence and Design (ISCID)

    Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models.

  • 2011 4th International Symposium on Computational Intelligence and Design (ISCID)

    Computational Intelligence techniques typically include Fuzzy Logic, Evolutionary Computation, Intelligent Agent Systems, Neural Networks, Cellular Automata, Artificial Immune Systems and other similar computational models. Computational Intelligence constitutes an umbrella of techniques, has proven to be flexible in decision making in dynamic environment.

  • 2010 3rd International Symposium on Computational Intelligence and Design (ISCID)

    ISCID 2010 will be held at Hangzhou, China in 29-31, October 2010. It provides researchers and practitioners interested in new information technologies an opportunity to highlight innovative research directions, novel applications, and a growing number of relationships between rough sets and such are as computational intelligence, knowledge discovery and design.

  • 2009 2nd International Symposium on Computational Intelligence and Design (ISCID)

    This symposium provide researchers and practitioners interested in new information technologies an opportunity to highlight innovative research directions, novel applications, and a growing number of relationships between rough sets and such areas as computational intelligence, knowledge discovery and data mining, non-conventional models of computation and design.

  • 2008 International Symposium on Computational Intelligence and Design (ISCID)

    computational intelligence, knowledge discovery and data mining, intelligent information systems, web mining, synthesis and analysis of complex objects , non-conventional models of computation and Industrial Design.


2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

The conference serves as the primary annual meeting for researchers in the field of human-robot interaction. The event will include a main papers track and additional sessions for posters, demos, and exhibits. Additionally, the conference program will include a full day of workshops and tutorials running in parallel.

  • 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchersin robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior,anthropology, and many other fields.

  • 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    This conference focuses on the interaction between humans and robots.

  • 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very bestresearch and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary,reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificialintelligence, organizational behavior, anthropology, and many other fields.

  • 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single-track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics.

  • 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    TOPICS: Robot companions, Lifelike robots, Assistive (health & personal care) robotics, Remote robots, Mixed initiative interaction, Multi-modal interaction, Long-term interaction with robots, Awareness and monitoring of humans, Task allocation and coordination, Autonomy and trust, Robot-team learning, User studies of HRI, Experiments on HRI collaboration, Ethnography and field studies, HRI software architectures

  • 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    * Robot companions * Lifelike robots * Assistive (health & personal care) robotics * Remote robots * Mixed initiative interaction * Multi-modal interaction * Long-term interaction with robots * Awareness and monitoring of humans * Task allocation and coordination * Autonomy and trust * Robot-team learning * User studies of HRI * Experiments on HRI collaboration * Ethnography and field studies * HRI software architectures

  • 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics Individual vs. group HRI

  • 2007 2nd Annual Conference on Human-Robot Interaction (HRI)


2017 14th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)

The 14th annual IEEE SECON conference will provide a unique forum to exchange innovative research ideas, recent results, and share experiences among researchers and practitioners in the field of sensing and communication in wireless networks. The focus of SECON is novel communication technologies and emerging applications and services, involving mobile sensing and communication, cyber-physical systems, and ubiquitous and pervasive computing.


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Periodicals related to Animal behavior

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Biomedical Circuits and Systems, IEEE Transactions on

The Transactions on Biomedical Circuits and Systems addresses areas at the crossroads of Circuits and Systems and Life Sciences. The main emphasis is on microelectronic issues in a wide range of applications found in life sciences, physical sciences and engineering. The primary goal of the journal is to bridge the unique scientific and technical activities of the Circuits and Systems ...


Biomedical Engineering, IEEE Transactions on

Broad coverage of concepts and methods of the physical and engineering sciences applied in biology and medicine, ranging from formalized mathematical theory through experimental science and technological development to practical clinical applications.


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Control Systems Technology, IEEE Transactions on

Serves as a compendium for papers on the technological advances in control engineering and as an archival publication which will bridge the gap between theory and practice. Papers will highlight the latest knowledge, exploratory developments, and practical applications in all aspects of the technology needed to implement control systems from analysis and design through simulation and hardware.


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Xplore Articles related to Animal behavior

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The Contrast and Inspiration of Animal Behavior and Traffic Behavior

Meng Chen; Fasheng Liu; Chengbao Wang 2012 Fifth International Symposium on Computational Intelligence and Design, 2012

This paper analyses the common characteristics and relevance of animal behavior and traffic behavior. It describes the feedback mechanism of animal behavior and the information process of traffic behavior from the point of view on automatic control, and then points out that the two behaviors are both controlled by themselves and environment. at last, by analyzing bats' echolocation system, this ...


Realization of an artificial pheromone system in random data carriers using RFID tags for autonomous navigation

Herianto; Daisuke Kurabayashi 2009 IEEE International Conference on Robotics and Automation, 2009

Navigation systems based on animal behavior have attracted considerable attention in the past few years. Navigation systems using artificial pheromones have not been extensively developed. Therefore, this paper presents a model for realizing an artificial pheromone system by using data carriers and autonomous robots. By introducing an artificial pheromone system composed of data carriers and autonomous robots, a robotics system ...


Wireless Inertial Sensors for Monitoring Animal Behavior

Subramaniam Venkatraman; John D. Long; Kristofer S. J. Pister; Jose M. Carmena 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007

Wireless sensors were designed which are small and light enough to be worn by small animals such as rats. These sensors are used to record three axes acceleration data from animals during natural behavior in a cage. The behavior of the animal is further extracted from the recorded acceleration data using neural network based pattern recognition algorithms. Successful recognition of ...


Self-aggregation in multi-agent shape control

Reza Haghighi; Chien Chern Cheah 2010 IEEE Conference on Robotics, Automation and Mechatronics, 2010

This paper presents a new interactive force in shape control to deal with group fragmentation during movement toward a desired shape. The proposed interactive force can maintain minimum distance between agents as well as group unity. Unlike other collective potential functions which have only one local minima, the proposed one has a local minima area which increase the flexibility of ...


Occurrence density index for behavior classification of zebrafish larvae

Qussay Al-Jubouri; Waleed Al-Nuaimy; Majid A. Al-Taee; Javier L. Luna; Lynne U. Sneddon 2016 13th International Multi-Conference on Systems, Signals & Devices (SSD), 2016

Larval zebrafish are proving to be promising subjects for research that is not subject to legal requirements. However, the behavior of this animal has not been fully explored by researchers yet. This paper proposes a new occurrence- density index (ODI) for behavioral analysis and classification of zebrafish larvae. The ODI is identified through a multistage process that includes (i) mapping ...


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Educational Resources on Animal behavior

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eLearning

The Contrast and Inspiration of Animal Behavior and Traffic Behavior

Meng Chen; Fasheng Liu; Chengbao Wang 2012 Fifth International Symposium on Computational Intelligence and Design, 2012

This paper analyses the common characteristics and relevance of animal behavior and traffic behavior. It describes the feedback mechanism of animal behavior and the information process of traffic behavior from the point of view on automatic control, and then points out that the two behaviors are both controlled by themselves and environment. at last, by analyzing bats' echolocation system, this ...


Realization of an artificial pheromone system in random data carriers using RFID tags for autonomous navigation

Herianto; Daisuke Kurabayashi 2009 IEEE International Conference on Robotics and Automation, 2009

Navigation systems based on animal behavior have attracted considerable attention in the past few years. Navigation systems using artificial pheromones have not been extensively developed. Therefore, this paper presents a model for realizing an artificial pheromone system by using data carriers and autonomous robots. By introducing an artificial pheromone system composed of data carriers and autonomous robots, a robotics system ...


Wireless Inertial Sensors for Monitoring Animal Behavior

Subramaniam Venkatraman; John D. Long; Kristofer S. J. Pister; Jose M. Carmena 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2007

Wireless sensors were designed which are small and light enough to be worn by small animals such as rats. These sensors are used to record three axes acceleration data from animals during natural behavior in a cage. The behavior of the animal is further extracted from the recorded acceleration data using neural network based pattern recognition algorithms. Successful recognition of ...


Self-aggregation in multi-agent shape control

Reza Haghighi; Chien Chern Cheah 2010 IEEE Conference on Robotics, Automation and Mechatronics, 2010

This paper presents a new interactive force in shape control to deal with group fragmentation during movement toward a desired shape. The proposed interactive force can maintain minimum distance between agents as well as group unity. Unlike other collective potential functions which have only one local minima, the proposed one has a local minima area which increase the flexibility of ...


Occurrence density index for behavior classification of zebrafish larvae

Qussay Al-Jubouri; Waleed Al-Nuaimy; Majid A. Al-Taee; Javier L. Luna; Lynne U. Sneddon 2016 13th International Multi-Conference on Systems, Signals & Devices (SSD), 2016

Larval zebrafish are proving to be promising subjects for research that is not subject to legal requirements. However, the behavior of this animal has not been fully explored by researchers yet. This paper proposes a new occurrence- density index (ODI) for behavioral analysis and classification of zebrafish larvae. The ODI is identified through a multistage process that includes (i) mapping ...


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IEEE-USA E-Books

  • How insects learn about the sun's course: alternative modeling approaches

    One of the major puzzles in animal behavior, arid a major problem to be solved in the design of robots, concerns how spatial patterns in the environment can be encoded internally and used for navigation in a complex natural environment. Most work on this issue has concerned landmark learning. This paper deals with a phenomenon of spatial learning that is at least as widespread in the animal world as landmark learning, but has received comparatively little attention. The phenomenon is the ability to learn the course of the sun relative to earth-bound features, and thus to use the sun as a true compass. After reviewing behavioral evidence from bees and ants, two particularly well studied species, we evaluate the applicability of symbolic and connectionist approaches to modeling the internal representation of this environmental pattern.

  • Towards a comprehensive Alife-model of the evolution of the nervous system and adaptive behavior

    The potentials and tools that are offered by Alife for biology in modeling the nervous system and animal behavior are mainly unexploited. There is no consistent Alife model of the biological evolution of the nervous system as yet. whereas the modeling tools are at hand and their application for this purpose seems evident. In a biologically grounded model we have to make every possible effort to use principles known from biology, and to minimize the arbitrarily employed organizing rules. The aim of our work is to create a biologically accurate Alife model of the formation and evolution of the nervous system in connection with the adaptive behavior. In this article we concentrate on the structure of the modeled genome, which is the basis of playing a double biological role: to ensure an open-ended evolutionary process, as well as to direct the ontogenesis. The main questions we examined are: what are the basic rules of construction that are sufficient to create a workable nervous system and how can we model them in a biologically realistic way?

  • A Bottom-Up Mechanism for Behavior Selection in an Artificial Creature

    In this paper we propose a mechanism for motivational competition and selection of behavior. One important characteristic of this mechanism is that the selection of behavior is modelled as an emergent property of a parallel process. This in contrast with mechanisms for behavior selection and motivational competition proposed earlier, which are based on a hierarchical. preprogrammed control structure. We show that selection of behavior can be modeled in a bottom-up way using an activation/inhibition dynamics among the different behaviors that can be selected. There is no weighing up of behaviors in a cognitive manner and neither are hierarchical or bureaucratic structures imposed. The paper elaborates upon the results we obtained with simulated creatures based on this mechanism. It draws parallels between characteristics observed in animal behavior and characteristics demonstrated by our artificial creatures. Examples are: displacement behavior, opportunistic behavior, fatigue, selective attention, and so on.

  • Modeling Adaptive Autonomous Agents

    One category of research in Artificial Life is concerned with modeling and building so-called adaptive autonomous agents, which are systems that inhabit a dynamic, unpredictable environment in which they try to satisfy a set of time-dependent goals or motivations. Agents are said to be adaptive if they improve their competence at dealing with these goals. based on experience. Autonomous agents constitute a new approach to the study of Artificial Intelligence (AI), which is highly inspired by biology, in particular ethology, the study of animal behavior. Research in autonomous agents has brought about a new wave of excitement into the field of AI. This paper reflects on the state of the art of this new approach. It attempts to extract its main ideas, evaluates what contributions have been made so far, and identifies its current limitations and open problems.

  • Index

    The effort to explain the imitative abilities of humans and other animals draws on fields as diverse as animal behavior, artificial intelligence, computer science, comparative psychology, neuroscience, primatology, and linguistics. This volume represents a first step toward integrating research from those studying imitation in humans and other animals, and those studying imitation through the construction of computer software and robots.Imitation is of particular importance in enabling robotic or software agents to share skills without the intervention of a programmer and in the more general context of interaction and collaboration between software agents and humans. Imitation provides a way for the agent -- -whether biological or artificial-- to establish a "social relationship" and learn about the demonstrator's actions, in order to include them in its own behavioral repertoire. Building robots and software agents that can imitate other artificial or human agents in an appropriate way involves complex problems of perception, experience, context, and action, solved in nature in various ways by animals that imitate.

  • Evolving Imitating Agents and the Emergence of a Neural Mirror System

    Imitation is a highly complex cognitive process, employing vision, perception, representation, memory and motor control. The underlying mechanisms that give rise to imitative behavior have attracted a lot of attention in recent years and have been the subject of research in various disciplines, from neuroscience to animal behavior and human psychology. In particular, studies in monkeys and humans have discovered a neural mirror system that demonstrates an internal correlation between the representations of perceptual and motor functionalities. In contradistinction to previous engineering-based approaches, we focus on the evolutionary origins of imitation and present a novel framework for studying the emergence of imitative behavior. We successfully develop evolutionary adaptive autonomous agents that spontaneously demonstrate imitative learning, facilitating a comprehensive study of the emerging underlying neural mechanisms. Interestingly, some of these agents are found to embody a neural "mirror" device analogous to those identified in biological systems. Further analysis of these agents' networks reveals complex dynamics, combining innate perceptual-motor coupling with acquired context-action associations, to accomplish the required task.

  • Toward Synthesizing Artificial Neural Networks that Exhibit Cooperative Intelligent Behavior: Some Open Issues in Artificial Life

    The tasks that animals perform require a high degree of intelligence. Animals forage for food, migrate, navigate, court mates, rear offspring, defend against predators, construct nests, and so on. These tasks commonly require social interaction/cooperation and are accomplished by animal nervous systems, which are the result of billions of years of evolution and complex developmental/learning processes. The Artificial Life (AL) approach to synthesizing intelligent behavior is guided by this biological perspective. In this article we examine some of the numerous open problems in synthesizing intelligent animal behavior (especially cooperative behavior involving communication) that face the field of AL, a discipline still in its infancy.

  • Contributors

    The effort to explain the imitative abilities of humans and other animals draws on fields as diverse as animal behavior, artificial intelligence, computer science, comparative psychology, neuroscience, primatology, and linguistics. This volume represents a first step toward integrating research from those studying imitation in humans and other animals, and those studying imitation through the construction of computer software and robots.Imitation is of particular importance in enabling robotic or software agents to share skills without the intervention of a programmer and in the more general context of interaction and collaboration between software agents and humans. Imitation provides a way for the agent -- -whether biological or artificial-- to establish a "social relationship" and learn about the demonstrator's actions, in order to include them in its own behavioral repertoire. Building robots and software agents that can imitate other artificial or human agents in an appropriate way involves complex problems of perception, experience, context, and action, solved in nature in various ways by animals that imitate.

  • Appendix

    The effort to explain the imitative abilities of humans and other animals draws on fields as diverse as animal behavior, artificial intelligence, computer science, comparative psychology, neuroscience, primatology, and linguistics. This volume represents a first step toward integrating research from those studying imitation in humans and other animals, and those studying imitation through the construction of computer software and robots.Imitation is of particular importance in enabling robotic or software agents to share skills without the intervention of a programmer and in the more general context of interaction and collaboration between software agents and humans. Imitation provides a way for the agent -- -whether biological or artificial-- to establish a "social relationship" and learn about the demonstrator's actions, in order to include them in its own behavioral repertoire. Building robots and software agents that can imitate other artificial or human agents in an appropriate way involves complex problems of perception, experience, context, and action, solved in nature in various ways by animals that imitate.

  • The Experimental Study and Computer Simulation of Fish Behavior in the Uniform Environment

    We have studied experimentally the carp exploratory behavior in the circular corridor under uniform illumination and in the absence of external landmarks. The behavior was not uniform despite the uniformity of environment The alternation of two modes of behavior, search (accompanied by high turn frequency) and ranging (with few or no turns), was observed. The existence of distinct modes manifested itself in the positive correlation between turn frequencies at successive time intervals, as well as in abrupt switching between high and low turn frequencies. We developed a model based on the one- dimension map: X n = λn X n−1 (1X n−1), where X is the tendency to turn, and parameter λ is influenced by Gaussian white noise caused by spontaneous nervous activity. There was a correlation between successive values of the tendency, as well as switches from series of low values to series of high ones under influence of the noise. The behavior of the model is the case of noise- induced phase transitions and matches experimental data qualitatively. It is concluded that a noise generated by the nervous system can play a role in the shaping of animal behavior.



Standards related to Animal behavior

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Jobs related to Animal behavior

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