Academic literature on the topic 'Animal intelligence'

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Journal articles on the topic "Animal intelligence"

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BAIDINS, ANDREJS. "Animal intelligence." Nature 319, no. 6050 (January 1986): 172. http://dx.doi.org/10.1038/319172b0.

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POWERS, R. "Animal intelligence." Nature 320, no. 6058 (March 1986): 104. http://dx.doi.org/10.1038/320104d0.

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FREMLIN, J. H. "Animal intelligence." Nature 316, no. 6031 (August 1985): 760. http://dx.doi.org/10.1038/316760a0.

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Hoag, Hannah. "Animal intelligence." Nature 441, no. 7092 (May 2006): 544–45. http://dx.doi.org/10.1038/nj7092-544a.

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Caryl, P. G. "Animal intelligence." Behaviour Research and Therapy 25, no. 1 (1987): 78. http://dx.doi.org/10.1016/0005-7967(87)90135-5.

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Cheney, D. "ANIMAL BEHAVIOR:Only Unthinking Intelligence?" Science 283, no. 5400 (January 15, 1999): 333. http://dx.doi.org/10.1126/science.283.5400.333.

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Lattal, Kennon A. "Where is “Animal Intelligence”?" Behavior Analyst 15, no. 1 (April 1992): 85–87. http://dx.doi.org/10.1007/bf03392590.

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Poli, M. D. "Animal learning and intelligence." Human Evolution 3, no. 6 (December 1988): 487–502. http://dx.doi.org/10.1007/bf02436334.

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Bruce, Darryl. "Puzzling Over Animal Intelligence." Contemporary Psychology: A Journal of Reviews 42, no. 10 (October 1997): 879–82. http://dx.doi.org/10.1037/000083.

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Gutiérrez Luna, Víctor Hugo, and Juan Reyes Juárez. "¿Hay realmente inteligencia animal? Una revisión filosófica." Sincronía XXV, no. 80 (July 3, 2021): 225–47. http://dx.doi.org/10.32870/sincronia.axxv.n80.11b21.

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In the context of philosophical research on animal intelligence, there are different traditions that deny that nonhuman animals are intelligent. In this article we mention some of these traditions, such as Cartesian mechanism and behaviorism. However, we will focus our attention on the proposals of the analytical philosophers John McDowell and Donald Davidson as representative of this philosophical tradition. His main idea is that by not having a language like that of human beings, the rest of the animals cannot be rational and, therefore, not intelligent either. Our position is that such an analytical tradition flatly ignores the scientific and philosophical evidence against it. We will give some relevant data in favor of animal intelligence. In addition, we will give an account of a trend that is manifested with increasing force among ethologists according to which there is a continuity between animal and human intelligence, considering the latter as the result of an evolutionary process and, therefore, as a result of a series of skills acquired by different species at some point in their formation.
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Dissertations / Theses on the topic "Animal intelligence"

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Alzu'Bi, Hamzah. "Analysis of human activities and animal behaviours based on computational intelligence." Thesis, University of Liverpool, 2015. http://livrepository.liverpool.ac.uk/2037039/.

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The study of behaviour is vital for animal welfare assessment in animal husbandry systems, exploring mechanisms of underlying diverse forms of behaviours and animal physiological and ecological interaction. Understanding animal behaviour is used in a systematic way to unlock and explore underlying functionalities of the brain which is one of the biggest challenges to science. This thesis introduces four novel applications for computational intelligence in human and animal behaviours. The four applications are: horse transport stress prediction system, human activity recognition, fish behaviour tracking and detection, and intelligent interactive fish feeding system. In the first application of human gait recognition, a practical, accurate and novel supervised learning system is proposed to recognize human activities. The proposed system uses single accelerometer device which makes the system practical to use and capable of being integrated with many commercially available devices. This work proposes highly accurate and practical human gait recognition system. In the second application of horse transport, a novel system is proposed to predict horse stress episodes during transport which enables a potential solution of horse stress by interfering at a suitable time. Dynamic nonlinear neural network is trained to predict horse stress time series given travel route and driving style time series. Horse transport is one of the most routinely stressful procedures in equine industry. In the third application of horse transport, a novel system for automatic fish tracking and behaviour recognition system is proposed. Fish are the second most popular experimental model behind mice in pharmaceuticals and biological research. Fish anxious behaviour could confound experiment outcomes. Fish behaviour could also be affected by invasive or non-invasive experiments in addition to other possible causes of distress. The proposed system consists of 3d real-time fish tracking, behaviour quantifying and recognition algorithms. Fish behaviour is estimated through fish swimming patterns. The system showed high accuracy recognition of fish behaviour in experiment where fish were exposed to a variety of external stimuli. In the fourth application of horse transport, an innovative smart fish feeding system is proposed. The fourth application of computational intelligence techniques addresses one of the major challenges in the fastest growing food sector industry worldwide, aquaculture industry. Most conventional fish feeding techniques are inefficient, cause environmental damage and fish losses, raise concerns regarding fish welfare and lead to non-uniform fish growth. Addressing these problems is a necessity for this industry to continue its growth. The novel feeding system is built based on fish behaviour which recognises, and assesses fish behaviours and interacts with fish to optimise the feeding process. Fish showed quick adaptation to this novel low-cost feeding system which proves the feasibly of implementing this system. The proposed system is expected to reduce food competition and environmental impact because of its responsive nature. Through novel applications of computational intelligence, this thesis has provided successful solutions for human and animal behaviour analysis research problems.
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Granovskiy, Boris. "Modeling Collective Decision-Making in Animal Groups." Doctoral thesis, Uppsala universitet, Matematiska institutionen, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-180972.

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Many animal groups benefit from making decisions collectively. For example, colonies of many ant species are able to select the best possible nest to move into without every ant needing to visit each available nest site. Similarly, honey bee colonies can focus their foraging resources on the best possible food sources in their environment by sharing information with each other. In the same way, groups of human individuals are often able to make better decisions together than each individual group member can on his or her own. This phenomenon is known as "collective intelligence", or "wisdom of crowds." What unites all these examples is the fact that there is no centralized organization dictating how animal groups make their decisions. Instead, these successful decisions emerge from interactions and information transfer between individual members of the group and between individuals and their environment. In this thesis, I apply mathematical modeling techniques in order to better understand how groups of social animals make important decisions in situations where no single individual has complete information. This thesis consists of five papers, in which I collaborate with biologists and sociologists to simulate the results of their experiments on group decision-making in animals. The goal of the modeling process is to better understand the underlying mechanisms of interaction that allow animal groups to make accurate decisions that are vital to their survival. Mathematical models also allow us to make predictions about collective decisions made by animal groups that have not yet been studied experimentally or that cannot be easily studied. The combination of mathematical modeling and experimentation gives us a better insight into the benefits and drawbacks of collective decision making, and into the variety of mechanisms that are responsible for collective intelligence in animals. The models that I use in the thesis include differential equation models, agent-based models, stochastic models, and spatially explicit models. The biological systems studied included foraging honey bee colonies, house-hunting ants, and humans answering trivia questions.
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Helme, Anne Elizabeth. "A comparison of intelligence in corvids and apes : implications for animal welfare." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612378.

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Childers, Lindsey. "Extending Human Compassion by Implementing Legal Rights for Animals." ScholarWorks@UNO, 2013. http://scholarworks.uno.edu/honors_theses/31.

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The purpose of this essay is to critically examine the current legal status of animals in the United States and offer possible alternatives to the current legal rights for animals. This essay examines the failures of the legal system in protecting animals that have abilities very similar to our own. With an examination of these types of animals, this essay will explain why some animals merit the status of legal personhood to protect them from being carelessly used by others. Ultimately, this essay is an attempt to open the field of legal protection for many animals starting with a few through legal personhood.
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Reid, Clio. "Exploration-avoidance and an anthropogenic toxin (lead Pb) in a wild parrot (kea: Nestor notabilis) : a thesis submitted to the Victoria University of Wellington in partial fulfilment of the requirements for the degree of Master of Science in Ecology and Biodiversity /." ResearchArchive@Victoria e-Thesis, 2008. http://hdl.handle.net/10063/897.

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Suits, William T. "Transitive inference and commonly coded stimuli." Click here to access thesis, 2005.

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Thesis (M.S.)--Georgia Southern University, 2005.
"A thesis submitted to the Graduate Faculty of Georgia Southern University in partial fulfillment of the requirements for the degree Master of Science" ETD. Includes bibliographical references (p. 32-34)
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Hyatt, Charles Winton. "Discrimination learning in the African elephant." Thesis, Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/28887.

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Hu, Dan. "Brain cytochrome oxidase activity related to vicaroius trial-and-error behavior during Y-maze learning in the rat /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Kelsall, A. "Flexible Shape Models for Marine Animal Detection in Underwater Images." Thesis, Honours thesis, University of Tasmania, 2005. https://eprints.utas.edu.au/248/1/afkThesis_FINAL.pdf.

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Many industries are benefiting from computer automation, however the area of image analysis is still limited. The process of finding a potential object in an image is hard in itself, let alone classifying it. Automating these tasks would significantly reduce the time it takes to complete them thus allowing much more data to be processed. This becomes a problem when data is collect faster than it can be analysed. Images and video sequences are captured for different purposes and need to be manually processed in order to discover their contents. The fishing industry is a perfect example of this. A fish farm needs to know the average size of the fish in a ring. At present, this involves either manually taking a sample of fish from the ring and measuring them, or taking a series of stereoscopic images and manually tracing a sample of fish. By using active shape models, the process of tracing a fish sample can be automated. The Active Shape Model (ASM) Toolkit is an implementation of active appearance models, an advanced type of active shape model. The wrapper application that was written as part of this research allows a more streamlined process to input region data into the ASM Toolkit for searching. Once a sample has been matched, it is possible to use the key points around it to base further calculations on such as its size and weight. The ASM Toolkit and the wrapper program demonstrate how the process of identifying a fish in an image can be automated and that it is possible to calculate the size and weight of fish. In an ideal manual test, the most effective model matched 68% of samples, and in the automated test matched 50% of the samples. If the program can run over several days collecting appropriate samples, the model will be able to match enough fish to estimate the average size and weight within a ring. It is shown that the types of samples used in training the model affects the performance more than the number of samples used.
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Ervin, Stephen. "The Animal/Man That Therefore I Am." Thesis, Stockholms universitet, Engelska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-98004.

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Grant Morrison’s Animal Man could be argued to worry the man/animal boundary. Using closereadings of the comics against the backdrop of Jacques Derrida’s and Martin Heidegger’stheories on the boundary between man and animal, I explore the following ideas which seemcommon in the discourses on that which separates humans from animals: intelligence vs. instinct,the human hand vs. the animal’s paw, humanity’s richness-in-world vs. animal’s poorness-inworld,and language.In Animal Man, Morrison gives voice to animal characters by giving them personalities,which seems a romanticizing of the real state of affairs. Alongside all the depicted animals, thereare many hybrid characters, which take on the characteristics of both humans and animals. Theuse of hybrid characters such as the Coyote and Animal Man problematize the boundary betweenman and animal. This study of Animal Man, most importantly, shows that the differences as wellas similarities between humans and animals are based on ideologically produced discourses, andthis includes Morrison’s own philosophy on animal rights and his activism. I argue that Morrisonboth worries the boundary between humans and animals, and keeps it operative in order to makethe reader perceive animals in more anthropocentric terms.
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Books on the topic "Animal intelligence"

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Clemmitt, Marcia. Animal Intelligence. 2455 Teller Road, Thousand Oaks California 91320 United States: CQ Press, 2010. http://dx.doi.org/10.4135/cqresrre20101022.

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Vauclair, Jacques. L' intelligence de l'animal. Paris: Seuil, 1992.

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Brad, Steiger, ed. Mysteries of animal intelligence. New York: TOR, 1995.

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Michael, Bright. Intelligence in animals. London: Reader's Digest, 1994.

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J, Hoage R., and Goldman Larry 1941-, eds. Animal intelligence: Insights into the animal mind. Washington, D.C: Smithsonian Institution Press, 1986.

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Esther, Bertram, and Francis John 1942-, eds. The truth about animal intelligence. New York: Tangerine Press, 2002.

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Page, George. Inside the animal mind. New York: Broadway Books, 2001.

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Wynne, Clive D. L. Do animals think? Princeton, N.J: Princeton University Press, 2004.

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Wynne, Clive D. L. Do animals think? Princeton, N.J: Princeton University Press, 2004.

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Wynne, Clive D. L. Do animals think? Princeton, N.J: Princeton University Press, 2004.

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Book chapters on the topic "Animal intelligence"

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Lexcellent, Christian. "Animal Intelligence." In Artificial Intelligence versus Human Intelligence, 51–52. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-21445-6_6.

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Lund, Nick. "Animal intelligence." In Intelligence and Learning, 35–56. London: Macmillan Education UK, 2010. http://dx.doi.org/10.1007/978-1-137-10932-3_3.

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Wordsworth, Anne M. "Animal Cognition and Animal Intelligence." In Law, Animals and Toxicity Testing, 1–17. London: Routledge, 2024. http://dx.doi.org/10.4324/9781032646350-1.

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Marchesini, Roberto. "Plural Intelligence." In The Creative Animal, 319–46. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07414-1_11.

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Lund, Nick. "Animal learning." In Intelligence and Learning, 11–34. London: Macmillan Education UK, 2010. http://dx.doi.org/10.1007/978-1-137-10932-3_2.

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Zentall, Thomas. "Intelligence." In Encyclopedia of Animal Cognition and Behavior, 1–18. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47829-6_778-1.

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Zentall, Thomas R. "Intelligence." In Encyclopedia of Animal Cognition and Behavior, 3596–614. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_778.

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Jahns, Gerhard. "Computational Intelligence to Recognize Animal Vocalization and Diagnose Animal Health Status." In Computational Intelligence in Intelligent Data Analysis, 239–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-32378-2_16.

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Byrne, Richard W. "Machiavellian Intelligence." In Encyclopedia of Animal Cognition and Behavior, 1–6. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-47829-6_781-1.

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Byrne, Richard W. "Machiavellian Intelligence." In Encyclopedia of Animal Cognition and Behavior, 4033–38. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-319-55065-7_781.

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Conference papers on the topic "Animal intelligence"

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Sakirin, Jakkawan, Thaniyaporn Rapeethasanaphong, and Parichat Maleewong. "Aquatic Animal Monitoring System." In IADC/SPE Asia Pacific Drilling Technology Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209933-ms.

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Abstract Aquatic Animal Monitoring Systemis initiated as part of PTTEP's Ocean for Life strategy as we thrive in enhancing Ocean Health & Biodiversity Monitoring to ensure that PTTEP's offshore operations are friendly and safe to the surrounding environment and aquatic animals. The basis of the Aquatic Animal Monitoring Systemproject focuses on conservation survey and tracking of rare aquatic animals as well as marinebiodiversity. As part of the process, an underwater camera was installed on a jacket leg of PTTEP's platform to allow the video recording of underwater lives. The video footage was then analyzed by Artificial Intelligence (AI)software using an object detection method for determining the animal's categorization, then using machine learning algorithm for more accuracy. This concept can visualize aquatic animals around the platform and the surrounding environment. Moreover, the AI software can shorten the video by cutting off any non-life appearing period. Therefore, this technique can support a processor during the video analysis from the platform, contributing to a better work efficiency as it can save time, manpower, and most importantly cost. For the detection algorithm, all targets generatea large amount of data in the form of images with labels in order to train a software to memorize the target objects. The AI software was able to detect and identify nine species of aquatic animals which are fish, turtle, whale, dolphin, shark, seal, sea lion, stingray, and seahorse. With AI software in place, the video raw file can be shortened up to 85% by removing non-life periods in the original video and tracking only animal life in the video frame. This is a significant milestone for PTTEP in creating sustainable values to the ocean, which is considered as PTTEP's second home. Adopting artificial intelligence and machine learning technology to this project, it helps categorizing aquatic animal types and shorten a videofile. Moreover, it can save manpower and time.
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Lum, Heather. "Human-Animal Teaming as a Model for Human-AI-Robot Teaming: Advantages and Challenges." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004183.

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Humans and animals have co-evolved for millions of years. The animal connection began with the exploitation and observation of animals by humans. Over time, regular social interactions were incorporated into the animal connection. This connection has also allowed us to utilize humans to help support and augment our skills and abilities; physically, emotionally, and cognitively. Of course, this relationship has changed over time as our connection and understanding of these animals’ capabilities has evolved as well as through the co-evolution of our species. At the same time, the future of human-autonomy teams shows a strong trend toward incorporating features to allow the human to engage with their robotic counterparts in a more natural way. Norman (2004) suggests that “products and systems that make you feel good are easier to deal with.” As the interfaces of robots, computers, and inanimate objects are designed to be more “intelligent,” humans may adapt the way they interact with, communicate, and think about such technology, treating objects more like humans. Humans (and many other animals) display a remarkably flexible and rich array of social competencies, demonstrating the ability to interpret, predict, and react appropriately to the behavior of others, as well as to engage others in a variety of complex social interactions. Developing computational systems that have these same sorts of social abilities is a critical step in designing robots, animated characters, and other computer agents that appear intelligent and capable in their interactions with humans (and each other), that can cooperate with people as capable partners, that are able to learn from natural human instruction, and that are intuitive and engaging for humans to interact with. Yet, today, many current technologies (animated agents, computers, etc.) interact with us in a manner characteristic of socially impaired people. In the best cases they know what to do, but often lack the social intelligence to do it in a socially appropriate manner. As a result, they frustrate us, and we quickly dismiss them even though they can be useful. It may instead be more useful to look at how humans interact and work with their animal counterparts. Like anthropomorphism, zoomorphism centers on attributing qualities to non-sentient beings; but in this case; it focuses on animal-like characteristics (Karanika & Hogg, 2020). In many contexts, teams are capable of solving complex problems well beyond the capacity of any one individual team member (Salas, Rosen, Burke, & Goodwin, 2009). However, not all teams are successful, and failures often come at a high cost. Why this is important is that humans often do not ascribe the same intelligence, consciousness, or abilities to animals as they do to humans and therefore may be less apt to get frustrated when it does not perform as expected. Also, understanding what different strengths and weaknesses each team member possesses will ultimately allow that team to be more successful. While animal-inspired designs have aided in improved robotic movement and manipulation, we maintain that design inspired by human-animal teaming can provide similar gains in robotic development, especially as it concerns improved human-robot interaction and teaming. As most people have far more experience interacting with animals than with robots, they are generally more able to recognize limitations in an animal’s ability to complete a task (Phillips, Ososky, Swigert, & Jentsch, 2012). In consequence, robotic designs inspired by human-animal relationships can lead to faster acceptance while fostering more effective interactions between humans and robots, as humans tap into well-established mental models, promote better understanding of near-future robots, and thus appropriately calibrate trust in near-future robotic teammates.
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Charles, P. Stephen, S. Dharmalingam, M. Baskaran, P. S. Manoharan, and G. R. Hemanth. "Intelligence Harmless Animal Avoider in Agriculture Farm." In 2023 International Conference on Computer Communication and Informatics (ICCCI). IEEE, 2023. http://dx.doi.org/10.1109/iccci56745.2023.10128580.

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Zhou, Hang, You Wu, Jiehong Li, Liangtao Pan, Hengzhou Ye, and Shuiwang Li. "Beyond animal detection: a benchmark for detecting animal age group." In 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), edited by Yuriy S. Shmaliy, Yougang Sun, Habib Zaidi, Hongying Meng, Hoshang Kolivand, Jianping Luo, and Mamoun Alazab. SPIE, 2023. http://dx.doi.org/10.1117/12.3009574.

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Prudhivi, Likhith, M. Narayana., Ch Subrahmanyam., M. Gopi Krishna., and Salim Chavan. "Animal Species Image Classification." In 2023 3rd International conference on Artificial Intelligence and Signal Processing (AISP). IEEE, 2023. http://dx.doi.org/10.1109/aisp57993.2023.10135017.

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Ramos-Fernández, Gabriel, Tania M. Palacios-Romo, and Sandra E. Smith Aguilar. "Exploring collective intelligence in animal fission-fusion dynamics." In The 2021 Conference on Artificial Life. Cambridge, MA: MIT Press, 2021. http://dx.doi.org/10.1162/isal_a_00415.

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Xiao, Austin, Ang Li, and Wyatt Bodle. "An Intelligent Plant and Animal Identification Mobile Application for Increased Biodiversity Awareness and Safety using Machine Learning." In 5th International Conference on Artificial Intelligence and Big Data. Academy & Industry Research Collaboration Center, 2024. http://dx.doi.org/10.5121/csit.2024.140433.

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Dangerous animal encounters have steadily increased over time and consumption of deadly plants is an important issue [12]. Our paper introduces a new mobile application that addresses the critical need for accurate animal and plant identification and classification to help mitigate safety risks for humans.With up to five million animal attacks reported every year in the United States alone, and over 100,000 cases of toxic plant exposure there is a need and a responsibility to increase awareness of the risks associated with animal and plant ignorance.Our proposed app utilizes innovative classification technologies, offering our users a swift and simple identification of both select plant and animal species.The app will relay information about the potential dangers and general facts about the classified animal [14].This will help our users to understand the environment they live in and to best prepare themselves against it.Some challenges with this proposal are curating a broad and efficient dataset, there are estimated to be eight million eukaryotic species which is unattainable for one dataset.We then had to decide which valuable information would be best to present without providing unwanted distractions in our user interface.We utilized Google Firebase to ensure secure authentication and data storage while using TensorFlow Lite to power the image classification.We then integrated all of this into flutter to create a friendly user interface and application that can run on both iOS and Android [15].Once our app was complete, we ran two experiments, one to test the accuracy of our classifications in plants and animals and another to test the effect of lower resolution images on classification accuracy.The experiments shed light on challenges and potential improvements for the application to help improve its efficiency as a tool for users to enhance their awareness, safety and understanding of the environment they live in.
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Kim, Jong-Hwan, Seung-Hwan Choi, Duckhwan Kim, Joonwoo Kim, and Minjoo Cho. "Animal-Robot Interaction for pet caring." In 2009 IEEE International Symposium on Computational Intelligence in Robotics and Automation - (CIRA 2009). IEEE, 2009. http://dx.doi.org/10.1109/cira.2009.5423214.

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Li, Sixu, Boyang Xiao, and Sixiong Xie. "Animal recognition using Siamese network with two kinds of backbone networks." In International Conference on Artificial Intelligence and Intelligent Information Processing (AIIIP 2022), edited by Pavel Loskot. SPIE, 2022. http://dx.doi.org/10.1117/12.2659594.

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Han, Shiwen, Qiuxin Gao, Chaoyu Wang, and Jiawei Zou. "Animal face classification based on deep learning." In 2021 2nd International Conference on Big Data & Artificial Intelligence & Software Engineering (ICBASE). IEEE, 2021. http://dx.doi.org/10.1109/icbase53849.2021.00067.

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Reports on the topic "Animal intelligence"

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Murray, Chris, Keith Williams, Norrie Millar, Monty Nero, Amy O'Brien, and Damon Herd. A New Palingenesis. University of Dundee, November 2022. http://dx.doi.org/10.20933/100001273.

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Robert Duncan Milne (1844-99), from Cupar, Fife, was a pioneering author of science fiction stories, most of which appeared in San Francisco’s Argonaut magazine in the 1880s and ’90s. SF historian Sam Moskowitz credits Milne with being the first full-time SF writer, and his contribution to the genre is arguably greater than anyone else including Stevenson and Conan Doyle, yet it has all but disappeared into oblivion. Milne was fascinated by science. He drew on the work of Scottish physicists and inventors such as James Clark Maxwell and Alexander Graham Bell into the possibilities of electromagnetic forces and new communications media to overcome distances in space and time. Milne wrote about visual time-travelling long before H.G. Wells. He foresaw virtual ‘tele-presencing’, remote surveillance, mobile phones and worldwide satellite communications – not to mention climate change, scientific terrorism and drone warfare, cryogenics and molecular reengineering. Milne also wrote on alien life forms, artificial immortality, identity theft and personality exchange, lost worlds and the rediscovery of extinct species. ‘A New Palingenesis’, originally published in The Argonaut on July 7th 1883, and adapted in this comic, is a secular version of the resurrection myth. Mary Shelley was the first scientiser of the occult to rework the supernatural idea of reanimating the dead through the mysterious powers of electricity in Frankenstein (1818). In Milne’s story, in which Doctor S- dissolves his terminally ill wife’s body in order to bring her back to life in restored health, is a striking, further modernisation of Frankenstein, to reflect late-nineteenth century interest in electromagnetic science and spiritualism. In particular, it is a retelling of Shelley’s narrative strand about Frankenstein’s aborted attempt to shape a female mate for his creature, but also his misogynistic ambition to bypass the sexual principle in reproducing life altogether. By doing so, Milne interfused Shelley’s updating of the Promethean myth with others. ‘A New Palingenesis’ is also a version of Pygmalion and his male-ordered, wish-fulfilling desire to animate his idealised female sculpture, Galatea from Ovid’s Metamorphoses, perhaps giving a positive twist to Orpheus’s attempt to bring his corpse-bride Eurydice back from the underworld as well? With its basis in spiritualist ideas about the soul as a kind of electrical intelligence, detachable from the body but a material entity nonetheless, Doctor S- treats his wife as an ‘intelligent battery’. He is thus able to preserve her personality after death and renew her body simultaneously because that captured electrical intelligence also carries a DNA-like code for rebuilding the individual organism itself from its chemical constituents. The descriptions of the experiment and the body’s gradual re-materialisation are among Milne’s most visually impressive, anticipating the X-raylike anatomisation and reversal of Griffin’s disappearance process in Wells’s The Invisible Man (1897). In the context of the 1880s, it must have been a compelling scientisation of the paranormal, combining highly technical descriptions of the Doctor’s system of electrically linked glass coffins with ghostly imagery. It is both dramatic and highly visual, even cinematic in its descriptions, and is here brought to life in the form of a comic.
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2

Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.

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The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. The most popular platform for mass information and social interaction is, first of all, network journalism, which is characterized by mobility and unlimited time and space. Authors have complete freedom to express their views in direct language, including their own word formation. Phonetic, lexical, phraseological and stylistic means of speech create expression of the text. A figurative word, a good aphorism or proverb, a paraphrased expression, etc. enhance the effectiveness of a multimedia text. This is especially important for headlines that simultaneously inform and influence the views of millions of readers. Given the wide range of issues raised by the Internet as a medium, research in this area is interdisciplinary. The science of information, combining language and social communication, is at the forefront of global interactions. The Internet is an effective source of knowledge and a forum for free thought. Nonlinear texts (hypertexts) – «branching texts or texts that perform actions on request», multimedia texts change the principles of information collection, storage and dissemination, involving billions of readers in the discussion of global issues. Mastering the word is not an easy task if the author of the publication is not well-read, is not deep in the topic, does not know the psychology of the audience for which he writes. Therefore, the study of media broadcasting is an important component of the professional training of future journalists. The functions of the language of the media require the authors to make the right statements and convincing arguments in the text. Journalism education is not only knowledge of imperative and dispositive norms, but also apodictic ones. In practice, this means that there are rules in media creativity that are based on logical necessity. Apodicticity is the first sign of impressive language on the platform of print or electronic media. Social expression is a combination of creative abilities and linguistic competencies that a journalist realizes in his activity. Creative self-expression is realized in a set of many important factors in the media: the choice of topic, convincing arguments, logical presentation of ideas and deep philological education. Linguistic art, in contrast to painting, music, sculpture, accumulates all visual, auditory, tactile and empathic sensations in a universal sign – the word. The choice of the word for the reproduction of sensory and semantic meanings, its competent use in the appropriate context distinguishes the journalist-intellectual from other participants in forums, round tables, analytical or entertainment programs. Expressive speech in the media is a product of the intellect (ability to think) of all those who write on socio-political or economic topics. In the same plane with him – intelligence (awareness, prudence), the first sign of which (according to Ivan Ogienko) is a good knowledge of the language. Intellectual language is an important means of organizing a journalistic text. It, on the one hand, logically conveys the author’s thoughts, and on the other – encourages the reader to reflect and comprehend what is read. The richness of language is accumulated through continuous self-education and interesting communication. Studies of social expression as an important factor influencing the formation of public consciousness should open up new facets of rational and emotional media broadcasting; to trace physical and psychological reactions to communicative mimicry in the media. Speech mimicry as one of the methods of disguise is increasingly becoming a dangerous factor in manipulating the media. Mimicry is an unprincipled adaptation to the surrounding social conditions; one of the most famous examples of an animal characterized by mimicry (change of protective color and shape) is a chameleon. In a figurative sense, chameleons are called adaptive journalists. Observations show that mimicry in politics is to some extent a kind of game that, like every game, is always conditional and artificial.
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