• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.524-539
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• 2022

With the advent of generative artificial intelligence technology, it became possible to create a virtual human, and produce a lecture video only with textual information. It is expected that the virtual human will enhance the efficient production of educational contents and the student's entertainment experience and satisfaction. However, there have been still few studies that have demonstrated the process of how virtual human technology reaches students' satisfaction. Therefore, the purpose of this study is to empirically examine whether the human likeness, which is the main characteristic of a virtual human based on Uncanny Valley theory, affects human experience and satisfaction. In particular, human likeness of the Uncanny Valley theory was subdivided into human likeness in the visual and verbal dimensions, and the process of reaching satisfaction was understood based on the experience economy model. In particular, human similarity in Uncanny Valley theory was classified as similarity in the visual and language levels, and the process of reaching satisfaction based on the experiential economic model was analyzed with a partial least squares structure model equation (PLS-SEM). The survey was conducted online for a panel of office workers at a specialized research institution in China. The results indicate that both the visual and verbal human likeness had a positive effect on experience economy factors (education, entertainment, esthetic, escape), and then these experiential factors had a significant effect on satisfaction. The results also provide some suggestions to consider when designing educational contents by virtual human.

• Journal of the Korea Society for Simulation
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• v.14 no.2
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• pp.93-103
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• 2005

This paper presents characteristics of a virtual human's navigation using a limited perception-based mapping. Previous approaches to virtual human navigation have used an omniscient perception requiring full layout of a virtual environment in advance. However, these approaches have a limitation on being a fundamental solution for a human-likeness of a virtual human, because behaviors of humans are basically based on their limited perception instead of omniscient perception. In this paper, we integrated Hill's mapping algorithm with a virtual human to experiment virtual human's navigation with the limited perception. This approach does not require full layout of the virtual environment, 360-degree's field of view, and vision through walls. In addition to static objects such as buildings, we consider enemy emergence that can affect an virtual human's navigation. The enemy emergence is used as the variable on the experiment of this present research. As the number of enemies varies, the changes in arrival rate and time taken to reach the goal position were observed. The virtual human navigates by two conditions. One is to take the shortest path to the goal position, and the other is to avoid enemies when the virtual human encounters them. The acquired result indicates that the virtual human's navigation corresponds to a human cognitive process, and thus this research can be a framework for human-likeness of virtual humans.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.1-10
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• 2010

This present paper's goal is to show a virtual human agent's movement-data loci based on realistically limited perception data is human-like. To determine human-likeness of the movement-data loci, we consider interactions between two parameters: Realistically Limited Perception (RLP) data and Incremental Movement-Path data Generation (IMPG). That is to consider how the former (i.e., RLP), one of the simulated parameters of human thought or its elements dictates the latter (i.e., IMPG), one of the simulated parameters of human movement behavior. Mapping DB is a prerequisite for navigation in an agent system because it functions as an interface between perception and movement behavior. Although Hill et al. studied mapping DB methodology based on RLP, their research dealt only with a rendering camera's view point data. The agent system in this present paper was integrated with the Hill's mapping DB module and then the two parameters' interaction was considered on a military reconnaissance mission with unexpected enemy emergence. Movement loci that were generated by the agent and subjects were compared with each other. The agent system in this present research verifies that it can be a functional test bed for producing human-like movement-data loci although the human-likeness of agent is the result of a pilot test, determined by two parameters (RLP and IMPG) and only 30 subjects.

• Journal of the Ergonomics Society of Korea
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• v.26 no.1
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• pp.47-53
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• 2007

The uncanny valley is a hypothesis about robotics concerning the emotional response of humans to robots and other non-human entities. Although it stands today as one of the robots and synthetic characters, the uncanny valley was speculative and few studies have been performed to test the theory. In two experiments, a total of 183 participants were employed to explore this hypothesis. The results of experiment 1 indicate that the perceived human likeness of a robot is not a key factor causing uncanny valley. And the results of experiments 2 suggest that even if the appearance and motion of a robot become fully human, the emotional response of humans could not reach human-human empathy levels.

• The Journal of Korea Robotics Society
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• v.3 no.4
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• pp.287-299
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• 2008

People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.19
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• pp.8155-8159
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• 2014

Background: Breast cancer is the serious health concern in India causing the highest mortality rate in females, which occurs due to uncontrolled cell division and can be metastasize to other parts of the human body. Interactions with estrogen receptor (ER) alpha are mainly responsible for the malignant tumors with regulation of the transcription of various genes as a transcription factor. Most of the drugs currently used for the breast cancer treatment produce various side effects and hence we focused on natural compounds which do not exhibit any toxic effect against normal human cells. Materials and Methods: Structure of human ER was retrieved from the Protein Data Bank and the structures of flavonoid compounds have been collected from PubChem database. Molecular docking and drug likeness studies were performed for those natural compounds to evaluate and analyze the anti-breast cancer activity. Results: Finally two compounds satisfying the Lipinski's rule of five were reported. The two compounds also exhibited highest binding affinity with human ER greater than 10.5 Kcal/mol. Conclusions: The results of this study can be implemented in the drug designing pipeline.

• Journal of Digital Convergence
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• v.14 no.10
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• pp.277-285
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• 2016

The purpose of this study is to quantitatively and empirically investigate whether cartoon-realism, which is referred to as a guideline for avoiding the uncanny valley phenomenon, is actually effective. An experiment was carried out to investigate whether or not methods that try to realistically express the texture of human skin while making 3D models whose outward appearance abstract like a cartoon actually reduce the negative sentiments associated with the uncanny valley phenomenon. The results found that when human skin textures were applied to cartoon-type 3D models, the degree of eeriness significantly increased (p<0.05), while there was no change in the degree of human likeness. When cartoon-style skin textures were applied to human-type 3D models, there was no significant difference in the degree of eeriness, but the degree of human likeness significantly decreased (p<0.05). These results show that, cartoon realism is not actually effective, and rather creates a perceptual conflict and induces the uncanny valley phenomenon. The results of this study are expected to be used as quantitative and empirical data for developing design guidelines that will overcome the uncanny valley phenomenon in the future.

• Natural Product Sciences
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• v.29 no.2
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• pp.104-112
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• 2023

COVID-19 caused a catastrophe in human health. People infected with COVID-19 also suffer from various clinical illnesses during and after the infection. The Boerhavia diffusa plant is well known for its antihypertensive activity. ACE-II inhibitors and calcium channel blockers are reported as mechanisms for the antihypertensive activity of B. diffusa phytoconstituents. Various studies have said ACE-II is the virus's binding site to attack host cells. COVID-19 treatment commonly employs a variety of synthetic antiviral and steroidal drugs. As a result, other clinical illnesses, such as hypertension and hyperglycemia, emerge as serious complications. Safe and effective drug delivery is a prime objective of the drug development process. COVID-19 is treated with various herbal treatments; however, they are not widely used due to their low potency. Many herbal plants and formulations are used to treat COVID-19 infection, in which B. diffusa is the most widely used plant. The current study relies on discovering active phytoconstituents with ACE-II inhibitory activity in the B. diffusa plant. As a result, it can be used as a treatment option for patients with COVID-19 and related diseases. Different phytoconstituents of the B. diffusa plant were selected from the reported literature. The activity of phytoconstituents against ACE-II proteins has been studied. Molecular docking and ligand-protein interaction computation tools are used in the in-silico experiment. Physicochemical, drug-likeness, water solubility, lipophilicity, and pharmacokinetic parameters are used to evaluate phytoconstituents. Liriodenine has the best drug-likeness, bioactivity, and binding score characteristics among the selected ligands. The in-silico study aims to find the therapeutic potential of B. diffusa phytoconstituents against ACE-II. Targeting ACE-II also shows an effect against SARS-CoV-2. It can serve as a rationale for designing a drug for patient infected with COVID-19 and associated diseases.

• 연구논문집
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• s.23
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• pp.73-80
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• 1993

This study presents an intelligent PID control method based on the fuzzy logic and this method is applied to the active magnetic bearing system. By using an appropriate fuzzy matrix, some changes of values of the three coefficients of the controller are determined during system operation and these lead to the improvement of the transient and steady state behavior of the closed loop system. The presented method is actually a combination of the principles of PID control and fuzzy logic. Since the fuzzy logic using linguistic variables in place of numeric variables has many points of likeness to the human logic, the improvement in performance is notable especially in case of large nonlinearity and uncertainty such as the controller start and the excessive mass unbalance. A set of simulation and experimental results illustrate and considerable improvement in the control performance including small overshoot and small transient currents in magnet coils, while maintaining the overal static and dynamic characteristics near the equilibrium position.