1,722,054 research outputs found
A new green pitviper of the Trimeresurus albolabris complex (Reptilia, Serpentes Viperidae) from central and southern Myanmar
No full textVogel, Gernot, Nguyen, Tan Van, David, Patrick (2023): A new green pitviper of the Trimeresurus albolabris complex (Reptilia, Serpentes Viperidae) from central and southern Myanmar. Zootaxa 5357 (4): 515-554, DOI: 10.11646/zootaxa.5357.4.3, URL: http://dx.doi.org/10.11646/zootaxa.5357.4.
Forecasting nonverbal social signals during Dyadic interactions with generative adversarial neural networks
No full textWe are approaching a future where social robots will progressively become widespread in many aspects of our daily lives, including education, healthcare, work, and personal use. All of such practical applications require that humans and robots collaborate in human environments, where social interaction is unavoidable. Along with verbal communication, successful social interaction is closely coupled with the interplay between nonverbal perception and action mechanisms, such as observation of gaze behaviour and following their attention, coordinating the form and function of hand gestures. Humans perform nonverbal communication in an instinctive and adaptive manner, with no effort. For robots to be successful in our social landscape, they should therefore engage in social interactions in a humanlike way, with increasing levels of autonomy. In particular, nonverbal gestures are expected to endow social robots with the capability of emphasizing their speech, or showing their intentions. Motivated by this, our research sheds a light on modeling human behaviors in social interactions, specifically, forecasting human nonverbal social signals during dyadic interactions, with an overarching goal of developing robotic interfaces that can learn to imitate human dyadic interactions. Such an approach will ensure the messages encoded in the robot gestures could be perceived by interacting partners in a facile and transparent manner, which could help improve the interacting partner perception and makes the social interaction outcomes enhanced
It takes two, not one: context-aware nonverbal behaviour generation in dyadic interactions
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Stakeholders’ perceptions of sustainable entrepreneurship within the context of a developing economy
No full textThis study advances the understanding of sustainable entrepreneurship (SE) by investigating stakeholders’ perceptions of SE’s dimensions in a developing economy. Sixty-three semi-structured interviews with local government officers and entrepreneurs in family business settings were conducted on three islands within the Vietnamese Marine Protected Areas cluster. The study fills both theoretical and empirical gaps concerning the emergence of SE in a developing economy. It empirically examines cultural sustainability and the interconnection between four sustainability pillars (environment, economy, society and culture), thus contributing to a more holistic concept of SE in the tourism sector. Furthermore, it reveals that stakeholders’ perceptions of SE are affected by levels of tourism development. The findings suggest important implications for family-owned businesses and policy makers
FIGURE 1 in A new green pitviper of the Trimeresurus albolabris complex (Reptilia, Serpentes Viperidae) from central and southern Myanmar
No full textFIGURE 1. Phylogenetic tree of the complex of species of Trimeresurus albolabris, modified from Zhu et al. (2016). Figure used with permission from P. Guo.Published as part of <i>Vogel, Gernot, Nguyen, Tan Van & David, Patrick, 2023, A new green pitviper of the Trimeresurus albolabris complex (Reptilia, Serpentes Viperidae) from central and southern Myanmar, pp. 515-554 in Zootaxa 5357 (4)</i> on page 516, DOI: 10.11646/zootaxa.5357.4.3, <a href="http://zenodo.org/record/10063602">http://zenodo.org/record/10063602</a>
FIGURE 5 in A new green pitviper of the Trimeresurus albolabris complex (Reptilia, Serpentes Viperidae) from central and southern Myanmar
No full textFIGURE 5. Distribution ranges of the species of the complex of Trimeresurus albolabris. Notes: numbers indicate different localities where the species have been recorded (see Appendix V for the details of localities).Published as part of <i>Vogel, Gernot, Nguyen, Tan Van & David, Patrick, 2023, A new green pitviper of the Trimeresurus albolabris complex (Reptilia, Serpentes Viperidae) from central and southern Myanmar, pp. 515-554 in Zootaxa 5357 (4)</i> on page 529, DOI: 10.11646/zootaxa.5357.4.3, <a href="http://zenodo.org/record/10063602">http://zenodo.org/record/10063602</a>
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Beyond text: multi-modal LLM in human robot interaction
No full textMultimodal interaction plays a vital role in Human-Robot Interaction (HRI), enabling robots to communicate with humans through multiple channels. This study introduces a novel approach to enhance such interactions by treating images and human motion as distinct foreign languages, in addition to text. In the proposed framework, vector quantization is employed to convert multimodal inputs such as images and human motions to an aligned set of tokens. A Large Language Model (LLM) is then pre-trained with the use of Low-Rank Adaptation (LoRA) and instruction-tuned on a dialogue dataset that incorporates both image and motion context. The proposed multimodal LLM framework aims to equip robots with the ability to understand and respond to complex human queries through multimodal inputs and outputs, enabling more natural and effective interactions
Learning Bodily Expression of Emotion for Social Robots through Human Interaction
Full text linkHuman facial and bodily expressions play a crucial role in human-human interaction to convey the communicator’s feelings. Being echoed by the influence of human social behavior, recent studies in human-robot interaction (HRI) have investigated how to generate emotional behaviors for social robots. Emotional behaviors can enhance user engagement, allowing the user to interact with robots in a transparent manner. However, they are ambiguous and affected by many factors such as personality traits, cultures, and environments. This paper focuses on developing the robot’s emotional bodily expressions adopting the user’s affective gestures. We propose the behavior selection and transformation model, enabling the robots to incrementally learn from the user’s gestures, to select the user’s habitual behaviors, and to transform the selected behaviors into the robot motions. The experimental results under several scenarios showed that the proposed incremental learning model endows a social robot with the capability of entering into a positive, long-lasting HRI. We have also confirmed that the robot can express emotions through the imitated motions of the user. The robot’s emotional gestures that reflected the interacting partner’s traits were widely accepted within the same cultural group, and perceptible across different cultural groups in different ways
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