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1

Sarstedt, Marko, Monika Imschloss et Susanne Adler. Multisensory Design of Retail Environments. Wiesbaden : Springer Fachmedien Wiesbaden, 2023. http://dx.doi.org/10.1007/978-3-658-41242-5.

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Davies, Christopher. Creating multisensory environments : Practical ideas for teaching and learning. Abingdon, Oxon : Routledge, 2012.

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Fowler, Susan. Multisensory rooms and environments : Controlled sensory experiences for people with profound and multiple disabilities. London : Jessica Kingsley Publishers, 2008.

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Zuidgeest, R. G. Multi-sensor data fusion in a distributed environment - architectural solutions -. Amsterdam : National Aerospace Laboratory, 1992.

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Baudoin, Y., et Maki H. Habib. Using robots in hazardous environments : Landmine detection, de-mining and other applications. Cambridge : Woodhead, 2011.

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6

IEEE Information Technology Conference (1998 Syracuse, N.Y.). 1998 IEEE Information Technology Conference : Information environment for the future ; showcasing leading edge information technologies, systems and strategies to meet military and commercial needs in the evolving information environment. Piscataway, NJ : IEEE, 1998.

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7

NATO Advanced Workshop on Scientific Support for the Decision Making in the Security Sector (2006 Velingrad, Bulgaria). Scientific support for the decision making in the security sector. Amsterdam : IOS Press, 2007.

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International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining (2009 Wuhan, China). International Symposium on Spatial Analysis, Spatial-Temporal Data Modeling, and Data Mining : 13-14 October 2009, Wuhan, China. Sous la direction de Liu Yaolin 1960-, Tang Xinming, Wuhan da xue. School of Resource and Environmental Science, China Jiao yu bu et SPIE (Society). Bellingham, Wash : SPIE, 2009.

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9

Pagliano, Paul. Multisensory Environments. David Fulton Publishers, 2017. http://dx.doi.org/10.4324/9781315831053.

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Pagliano, Paul. Multisensory Environments. Fulton Publishers, David, 2017.

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Pagliano, Paul. Multisensory Environments. Fulton Publishers, David, 2017.

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Pagliano, Paul. Multisensory Environments. Fulton Publishers, David, 2017.

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Pagliano. Multisensory Environments. David Fulton Publish, 1999.

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Pagliano, Paul. Multisensory Environments. Fulton Publishers, David, 2017.

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15

Fowler, Susan. Multisensory Rooms and Environments : Controlled Sensory Experiences for People With Profound and Multiple Disabilities. Jessica Kingsley Publishers, 2008.

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Fowler, Susan, et Paul Pagliano. Multisensory Rooms and Environments : Controlled Sensory Experiences for People with Profound and Multiple Disabilities. Kingsley Publishers, Jessica, 2008.

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17

and, Bruno. Perception for Action. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198725022.003.0003.

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Our bodies are not static, and multisensory signals are constantly being processed to produce motor behaviours. This chapter will discuss how multisensory interactions shape three kinds of such behaviours: reaching and grasping objects with the hand, walking, and maintaining one’s posture. Motor control is inherently multisensory, as it involves combining anticipatory sensory signals from vision and proprioception, as well as, in some cases, other sensory channels, to prepare movements before they are actually initiated, and then combining online multisensory feedback to control movements while they are being executed. In addition, multisensory motor processes turn out to be important in understanding how we perceive agency, the awareness that our own minds are the agents that will allow our actions to take place, how we adapt to novel sensory environments, how we understand actions performed by others exploiting ‘mirror’ sensorimotor brain systems, and perhaps even why we can’t tickle ourselves.
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Pagliano, Paul. Using a Multisensory Environment. David Fulton Publishers, 2013. http://dx.doi.org/10.4324/9781315069067.

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Butz, Martin V., et Esther F. Kutter. Multisensory Interactions. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780198739692.003.0010.

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This chapter shows that multiple sensory information sources can generally be integrated in a similar fashion. However, seeing that different modalities are grounded in different frames of reference, integrations will focus on space or on identities. Body-relative spaces integrate information about the body and the surrounding space in body-relative frames of reference, integrating the available information across modalities in an approximately optimal manner. Simple topological neural population encodings are well-suited to generate estimates about stimulus locations and to map several frames of reference onto each other. Self-organizing neural networks are introduced as the basic computation mechanism that enables the learning of such mappings. Multisensory object recognition, on the other hand, is realized most effectively in an object-specific frame of reference – essentially abstracting away from body-relative frames of reference. Cognitive maps, that is, maps of the environment are learned by connecting locations over space and time. The hippocampus strongly supports the learning of cognitive maps, as it supports the generation of new episodic memories, suggesting a strong relation between these two computational tasks. In conclusion, multisensory integration yields internal predictive structures about spaces and object identities, which are well-suited to plan, decide on, and control environmental interactions.
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and, Bruno. A Multisensory Perspective. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198725022.003.0001.

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Perception may be defined as the cognitive process that lets us know what is out there, based on incoming sensory signals. Standard textbook accounts often emphasize five modular ‘senses’ encoding such signals. In the perspective presented in this book, instead, perception is inherently multisensory and linked to exploratory action. Perceptual processes do not merely encode incoming sensory signals, they actively explore the environment, seeking informative stimulation from potential multisensory sources and they combine available signals through several multisensory interactions. Studying perception within a multisensory, rather than modular perspective, requires a systemic approach, and this book illustrates how this notion can be successfully applied to eight domains of perception in natural conditions: knowing our own body, controlling its movements, perceiving inanimate objects, perceiving edible objects, understanding the intriguing phenomenon known as synaesthesia, attending to objects in multisensory conditions, perceiving space, and perceiving time.
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Pagliano, Paul. Using a Multisensory Environment : A Practical Guide for Teachers. Fulton Publishers, David, 2013.

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Pagliano, Paul. Using a Multisensory Environment : A Practical Guide for Teachers. Fulton Publishers, David, 2013.

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Pagliano, Paul. Using a Multisensory Environment : A Practical Guide for Teachers. Fulton Publishers, David, 2013.

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Pagliano, Paul. Using a Multisensory Environment : A Practical Guide for Teachers. Fulton Publishers, David, 2013.

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O'Callaghan, Casey. A Multisensory Philosophy of Perception. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198833703.001.0001.

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This book argues that human perception and perceptual consciousness are richly multisensory. Its thesis is that the coordinated use of multiple senses enhances and extends human perceptual capacities and consciousness in three critical ways. First, crossmodal perceptual illusions reveal hidden multisensory interactions that typically make the senses more coherent and reliable sources of evidence about the environment. Second, the joint use of multiple senses discloses more of the world, including novel features and qualities, making possible new forms of perceptual experience. Third, through crossmodal dependence, plasticity, and perceptual learning, each sense is reshaped by the influence of others, at a time and over time. The implication is that no sense—not even vision itself—can be understood entirely in isolation from the others. This undermines the prevailing approach to perception, which proceeds sense by sense, and sets the stage for a revisionist multisensory approach that illuminates the nature, scope, and character of sense perception.
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Fahmy, Alaa Eldin M. Horizontal estimation and information fusion in multitarget and multisensor environments. 1987.

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Pagliano, Paul. Using a Multisensory Environment : A Practical Guide for Teachers (Resources for Teachers). David Fulton Publish, 2001.

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28

Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2020.

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Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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32

Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. CRC Press, 2018. http://dx.doi.org/10.1201/9781315154602.

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Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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Chang, Ni-Bin, et Kaixu Bai. Multisensor Data Fusion and Machine Learning for Environmental Remote Sensing. Taylor & Francis Group, 2018.

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35

Brady, Emily. Aesthetic Value, Nature, and Environment. Sous la direction de Stephen M. Gardiner et Allen Thompson. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780199941339.013.17.

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This chapter discusses key issues and questions about aesthetic experience and valuing of natural objects, processes, and phenomena. It begins by exploring the character of environmental, multisensory aesthetic appreciation and then examines the central debate between “scientific cognitivism” and “noncognitivism” in contemporary environmental aesthetics. In assessing this debate and the place of knowledge, imagination, and emotion in aesthetic valuing, it is argued that non-cognitive approaches have the advantage of supporting a critical pluralism that recognizes the variety and breadth of aesthetic engagement with nature. Interactions between aesthetic and ethical values are also discussed, especially with respect to their role in philosophical positions such as “aesthetic preservationism” and the call for developing aesthetic theories that are consistent with environmentalism.
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Gogate, Lakshmi. Multisensory Perception and Communication : Brain, Behaviour, Environment Interaction, and Development in the Early Years. Taylor & Francis Group, 2018.

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Gogate, Lakshmi. Multisensory Perception and Communication : Brain, Behaviour, Environment Interaction, and Development in the Early Years. Taylor & Francis Group, 2018.

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Gogate, Lakshmi. Multisensory Perception and Communication : Brain, Behaviour, Environment Interaction, and Development in the Early Years. Taylor & Francis Group, 2018.

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Gogate, Lakshmi. Multisensory Perception and Communication : Brain, Behaviour, Environment Interaction, and Development in the Early Years. Taylor & Francis Group, 2018.

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40

Claramunt, Christophe, Vasily Popovich, Manfred Schrenk et Kyrill Korolenko. Information Fusion and Geographic Information Systems : Environmental and Urban Challenges. Springer London, Limited, 2013.

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Claramunt, Christophe, Vasily Popovich, Manfred Schrenk et Kyrill Korolenko. Information Fusion and Geographic Information Systems : Environmental and Urban Challenges. Springer, 2013.

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Claramunt, Christophe, Vasily Popovich, Manfred Schrenk et Kyrill Korolenko. Information Fusion and Geographic Information Systems : Environmental and Urban Challenges. Springer, 2016.

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43

and, Bruno. Object Perception and Recognition. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198725022.003.0004.

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Perceived objects are unitary entities that enter our consciousness as organized wholes distinct from other entities and from empty parts of the environment, that are amenable to bodily interactions, and that possess several features such as a three-dimensional structure, a location in space, a colour, a texture, a weight, a degree of rigidity, an odour, and so on. In this chapter, we will discuss perceptual processes responsible for forming such units within and between sensory channels, typically for the purpose of recognition. Our discussion of multisensory interactions in object perception will provide a useful domain for illustrating the key notion of optimal multisensory integration and for introducing Bayesian models of perception. These models provide important novel ways of addressing classical problems in the philosophy of perception, in influential historical approaches such as the Gestalt theory of perception, and in applications to rehabilitation based on sensory substitution.
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Castellanos, Irina, David B. Pisoni, Chen Yu, Chi-hsin Chen et Derek M. Houston. Embodied Cognition in Prelingually Deaf Children with Cochlear Implants. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190880545.003.0017.

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The theory of embodiment postulates that cognition emerges from multisensory interactions of an agent with its environment and as a result of multiple overlapping and time-locked sensory-motor activities. In this chapter, we discuss the complex multisensory system that may underlie young children’s novel word learning, how embodied attention may provide new insights into language learning after prelingual hearing loss, and how embodied attention may underlie learning in the classroom. We present new behavioral data demonstrating the coordination of sensory-motor behaviors in groups of young children with prelingual hearing loss (deaf, early implanted children with cochlear implants and hard-of-hearing children with hearing aids) and without hearing loss (two control groups of peers matched for chronological and hearing age). Our preliminary findings suggest that individual differences and variability in language outcomes may be traced to children’s coordination of auditory, visual, and motor behaviors with a social partner.
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Baudoin, Y., et M. K. Habib. Using Robots in Hazardous Environments : Landmine Detection, de-Mining and Other Applications. Elsevier Science & Technology, 2010.

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Heimler, Benedetta, Francesco Pavani et Amir Amedi. Implications of Cross-Modal and Intramodal Plasticity for the Education and Rehabilitation of Deaf Children and Adults. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190880545.003.0015.

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Exploring the environment without the auditory modality elicits wholesale reorganizations at both the behavioral and the neural levels throughout life. This chapter reviews changes in brain organization and behavior arising from early deafness. It depicts a multifaceted framework in both domains: the performance of deaf persons has been shown to be comparable to, better than, as well as worse than that of hearing participants. They also show brain modifications ascribable both to intramodal (within the visual system) and cross-modal plasticity (the recruitment of the deprived auditory cortex by intact sensory modalities). The authors discuss the implications of these results for sensory rehabilitation and highlight the benefits of multisensory systematic training programs to boost recovery.
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1998 IEEE Information Technology Conference : Information Environment for the Future ; Showcasing Leading Edge Information Technologies, Systems and Str. Institute of Electrical & Electronics Enginee, 1998.

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and, Bruno. Perceiving Your Own Body. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198725022.003.0002.

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The perception of our own body is a defining characteristic of our sense of self and a prerequisite for interacting with the environment and guiding movements. In the traditional view, the body is perceived mostly through somatosensation. However, experimental results are increasingly demonstrating that visual and vestibular signals also play an important role in body perception, that somatosensation in body perception is not limited to touch as traditionally conceived but may also include signals from the interior of the body (interoception), and, perhaps most surprisingly, that how we perceive and represent our body can be rapidly altered by novel combinations of multisensory stimuli. These findings have important implications for our understanding of neurological impairments of body representation and for their rehabilitation.
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