scholarly journals Communication with Self-Growing Character to Develop Physically Growing Robot Toy Agent

2020 ◽  
Vol 10 (3) ◽  
pp. 923
Author(s):  
Mingu Lee ◽  
Jiyong Kim ◽  
Hyunsu Jeong ◽  
Azure Pham ◽  
Changhyeon Lee ◽  
...  
Keyword(s):  
Facial Expression ◽  
Mental Model ◽  
Physical Growth ◽  
Emotional Expressions ◽  
Research Approach ◽  
Evidence Based ◽  
Design Studies ◽  
One Dimensional ◽  
Participatory Behavior ◽  
Product Design Process

Robots for communication are developed extensively with an emphasis on sympathy. This study deals with the growth of character and the control of its operation. The child has time to be alone with the nature of his/her robot friend. That child can interact with other people’s emotional expressions through a robot. Step by step, the robot character will grow as the child grows. Through design studies, qualitative processes such as customer experience audit, eye tracking, mental model diagrams, and semantic differences have been executed for the results. The participatory behavior research approach through user travel is mapped from the user’s lead to the evidence-based design. This research considers how synthetic characteristics can be applied to the physical growth of robot toys through the product design process. With the development of robot toy “Buddy”, two variations on the robot were made to achieve recognizable growth. (1) one-dimensional height scaling and (2) facial expression including the distance between two eyes on the screen. Observations represented children’s reactions when "Buddy" was released with the children. As an independent synthetic character, the robot was recognized by children who had the designed function. Robots for training may require more experimentation.

scholarly journals Communication with Self-growing Character to Develop Physically Growing Robot Toy Agent

2019 ◽  
Author(s):  
Mingu Lee ◽  
Jiyong Kim ◽  
Hyunsu Jeong ◽  
Azure Pham ◽  
Changhyeon Lee ◽  
...  
Keyword(s):  
Facial Expression ◽  
Mental Model ◽  
Physical Growth ◽  
Emotional Expressions ◽  
Research Approach ◽  
Evidence Based ◽  
Design Studies ◽  
One Dimensional ◽  
Participatory Behavior ◽  
Product Design Process

Robots for communication are developed extensively with emphasis on sympathy. This study deals with the growth of character and the control of its operation accordingly. The child has time to be alone with the nature of his/her robot friend. The child can interact with other people's emotional expressions through a robot. Step by step, the robot character will grow as the child grows. Through design studies, qualitative processes such as {customer experience audit, eye tracking, mental model diagrams, semantic differences} have been executed for the results. The participatory behavior research approach through user travel is mapped from the user's lead to the evidence-based design. This research considers how the synthetic characteristics can be applied to the physical growth of robot toys through the product design process. With the development of robot toy "Buddy", we tried making two variations on the robot to achieve recognizable growth. (1) An one-dimensional height scaling and (2) facial expression including the distance between two eyes on the screen. Observations represented children's reactions when "Buddy" was released to with the children. As an independent synthetic character, the robot was recognized by children who had the designed function. Robots for training may require more experimentation.

Capacity-Free Automatic Processing of Facial Expressions of Emotion

2020 ◽  
Author(s):  
Joshua W Maxwell ◽  
Eric Ruthruff ◽  
michael joseph
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Face Processing ◽  
Emotional Expressions ◽  
Facial Expression Of Emotion ◽  
Expression Of Emotion ◽  
Facial Expressions Of Emotion ◽  
Correspondence Effect ◽  
Experimental Logic ◽  
Face Task

Are facial expressions of emotion processed automatically? Some authors have not found this to be the case (Tomasik et al., 2009). Here we revisited the question with a novel experimental logic – the backward correspondence effect (BCE). In three dual-task studies, participants first categorized a sound (Task 1) and then indicated the location of a target face (Task 2). In Experiment 1, Task 2 required participants to search for one facial expression of emotion (angry or happy). We observed positive BCEs, indicating that facial expressions of emotion bypassed the central attentional bottleneck and thus were processed in a capacity-free, automatic manner. In Experiment 2, we replicated this effect but found that morphed emotional expressions (which were used by Tomasik) were not processed automatically. In Experiment 3, we observed similar BCEs for another type of face processing previously shown to be capacity-free – identification of familiar faces (Jung et al., 2013). We conclude that facial expressions of emotion are identified automatically when sufficiently unambiguous.

Technology-Mediated Collaboration, Shared Mental Model and Task Performance

2012 ◽  
Vol 24 (1) ◽  
pp. 64-81 ◽  
Author(s):  
Hayward P. Andres
Keyword(s):  
Social Influence ◽  
Direct Observation ◽  
Mental Model ◽  
Social Impact ◽  
Model Development ◽  
Research Approach ◽  
Team Process ◽  
Shared Mental Model ◽  
Team Productivity ◽  
The Impact

This study takes a direct observation research approach to examine how the impact of collaboration mode on team productivity and process satisfaction is mediated by shared mental model. Team cognition and social impact theories are integrated to provide a framework for explaining how technology-mediated collaboration constrains or enhances team shared mental model development and its subsequent impact on task outcomes. Partial least squares analysis revealed that technology-mediated collaboration impacts shared mental model development. The results also demonstrate that timely and accurate development of shared mental model facilitates increases in both productivity and team process satisfaction. Direct observation of team process behaviors suggests that collaboration modes differ not only in their impact on communication facilitation but efficacy-based, motivational, and social influence factors (e.g., self-efficacy and team-efficacy, perceived salience and credibility of contributions, social influence on action, etc.) as well. Shared mental model development requires quality communication among team members that are motivated to participate by a positive team climate that promotes idea convergence.

scholarly journals Deconstruction of minimalist residential design development practice in South Kuta

2020 ◽  
Vol 6 (2) ◽  
pp. 28-35
Author(s):  
I Made Pande Artadi ◽  
A. A. Ngurah Anom Kumbara ◽  
Putu Rumawan Salain ◽  
Ida Bagus Gde Pujaastawa
Keyword(s):  
Residential Buildings ◽  
Lifestyle Changes ◽  
Research Approach ◽  
Analysis Method ◽  
Design Development ◽  
Design Studies ◽  
Residential Design ◽  
Massive Scale ◽  
Depth Interviews ◽  
Development Practice

Minimalist residential develops was received massively in the middle of Balinese society, carrying the values ​​of modernity by prioritizing function, the strength of ratio, and ignoring the past (ahistoric). The development and acceptance of these residences were contrary to Bali Provincial Regulation No. 05/2005 which requires residential buildings to display Balinese style. Massive acceptance of minimalist residential has implications in the dimensions of Balinese environmental, social, and cultural identity. The purpose of the study was to uncover the factors underlying the development and acceptance of minimalist dwelling in South Kuta. The research approach used was the cultural studies and design studies approach. The type of data collected was qualitative data obtained through observation, in-depth interviews, reading, and document checking. All data were analyzed using the qualitative interpretative analysis method. To understand and interpret the data, theories of deconstruction, consumerism, semiotics and identity theory are used. The results revealed that the development and acceptance of a minimalist residential design on a massive scale in South Kuta was due to the factor of capitalism and lifestyle changes.

Evidence-Based Structural Uncertainty Quantification by Dimension Reduction Decomposition and Marginal Interval Analysis

2019 ◽  
Vol 142 (5) ◽  
Author(s):  
Lixiong Cao ◽  
Jie Liu ◽  
Chao Jiang ◽  
Zhantao Wu ◽  
Zheng Zhang
Keyword(s):  
Dimension Reduction ◽  
Uncertainty Quantification ◽  
Interval Analysis ◽  
Evidence Theory ◽  
Evidence Based ◽  
Original Performance ◽  
Engineering Applications ◽  
Performance Function ◽  
One Dimensional ◽  
Interval Analysis Method

Abstract Evidence theory has the powerful feature to quantify epistemic uncertainty. However, the huge computational cost has become the main obstacle of evidence theory on engineering applications. In this paper, an efficient uncertainty quantification (UQ) method based on dimension reduction decomposition is proposed to improve the applicability of evidence theory. In evidence-based UQ, the extremum analysis is required for each joint focal element, which generally can be achieved by collocating a large number of nodes. Through dimension reduction decomposition, the response of any point can be predicted by the responses of corresponding marginal collocation nodes. Thus, a marginal collocation node method is proposed to avoid the call of original performance function at all joint collocation nodes in extremum analysis. Based on this, a marginal interval analysis method is further developed to decompose the multidimensional extremum searches for all joint focal elements into the combination of a few one-dimensional extremum searches. Because it overcomes the combinatorial explosion of computation caused by dimension, this proposed method can significantly improve the computational efficiency for evidence-based UQ, especially for the high-dimensional uncertainty problems. In each one-dimensional extremum search, as the response at each marginal collocation node is actually calculated by using the original performance function, the proposed method can provide a relatively precise result by collocating marginal nodes even for some nonlinear functions. The accuracy and efficiency of the proposed method are demonstrated by three numerical examples and two engineering applications.

scholarly journals Local feature extraction based facial emotion recognition: a survey

2020 ◽  
Vol 10 (4) ◽  
pp. 4080
Author(s):  
Khadija Slimani ◽  
Mohamed Kas ◽  
Youssef El Merabet ◽  
Yassine Ruichek ◽  
Rochdi Messoussi
Keyword(s):  
Facial Expression ◽  
Large Scale ◽  
State Of The Art ◽  
Research Work ◽  
Emotional Expressions ◽  
Expression Recognition ◽  
Technological Advancement ◽  
Recognition Systems ◽  
Local Feature Extraction ◽  
Micro Patterns

Notwithstanding the recent technological advancement, the identification of facial and emotional expressions is still one of the greatest challenges scientists have ever faced. Generally, the human face is identified as a composition made up of textures arranged in micro-patterns. Currently, there has been a tremendous increase in the use of local binary pattern based texture algorithms which have invariably been identified to being essential in the completion of a variety of tasks and in the extraction of essential attributes from an image. Over the years, lots of LBP variants have been literally reviewed. However, what is left is a thorough and comprehensive analysis of their independent performance. This research work aims at filling this gap by performing a large-scale performance evaluation of 46 recent state-of-the-art LBP variants for facial expression recognition. Extensive experimental results on the well-known challenging and benchmark KDEF, JAFFE, CK and MUG databases taken under different facial expression conditions, indicate that a number of evaluated state-of-the-art LBP-like methods achieve promising results, which are better or competitive than several recent state-of-the-art facial recognition systems. Recognition rates of 100%, 98.57%, 95.92% and 100% have been reached for CK, JAFFE, KDEF and MUG databases, respectively.

Staff participation in design with multiple tools: Impact on design and POE results

2021 ◽  
pp. 193758672110607
Author(s):  
Tiina Jouppila
Keyword(s):  
Online Survey ◽  
Research Study ◽  
Healthcare Providers ◽  
Evidence Based ◽  
Staff Satisfaction ◽  
Healthcare Staff ◽  
Design Studies ◽  
Significant Difference ◽  
Technical Solutions ◽  
The Impact

Objective: This is a concluding part of an action research study to evaluate the impact on healthcare staff participation in the design of a new intensive care unit (ICU). Staff participated with multiple tools in the design; during the predesign phase utilizing co-design and virtual mock-ups, and also participating in the predesign evaluation (PDE) and postoccupancy evaluation (POE). Both the ICU design and evaluations were based on the principles of evidence-based design studies. Method: Staff satisfaction was evaluated with an online survey comprising 116 statements on 13 different topics used both in PDE and POE. There was space for open-ended comments after each topic. Results: There was a statistically significant difference (<.001) between PDE and POE results. There were considerable improvements in privacy, accessibility, safety and security, and acoustics. It was assumed that participation in the predesign phase would positively influence POE results, but there were no statistical differences in any topics. However, as a result of collaborative predesign phase, the staff was satisfied with these jointly designed patient rooms. Open-ended questions revealed the importance to continue functional and technical support for staff after commissioning and ensure that technical solutions are practical and well-functioning. Conclusion: The use of PDE and POE assists to set predetermined criteria and evaluate the success of design. Healthcare providers should see POE as a valuable part of design and commissioning process. Additionally, the use of POE should be made more effortless and the results more easily accessible to promote increased interest and usage.

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