• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.503-512
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• 2014

People would like to be socially engaged not only with humans but also with robots. One of the most common ways in the robotic field to enhance human robot interaction is to use emotion and integrate emotional concepts into robots. Many researchers have been focusing on developing a robot's emotional expressions. However, it is first necessary to establish the psychological background of a robot's emotion generation model in order to implement the whole process of a robot's emotional behavior. Therefore, this article suggests a robot's motivational emotion model with value effectiveness from a Higgins' motivation definition, regulatory focus theory, and Circumplex model. For the test, a game with the best-two-out-of-three rule is introduced. Each step of the game was evaluated by the proposed model. As the results imply, the proposed model generated psychologically appropriate emotions for a robot in the given situation. The empirical survey remains for future work to prove that this research improves social human robot interaction.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.4
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• pp.221-228
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• 2023

Physical and mental changes caused by emotions can affect various behaviors, such as driving or learning behavior. Therefore, recognizing these emotions is a very important task because it can be used in various industries, such as recognizing and controlling dangerous emotions while driving. In this paper, we attempted to solve the emotion recognition task by implementing a multimodal model that recognizes emotions using both audio and video data from different domains. After extracting voice from video data using RAVDESS data, features of voice data are extracted through a model using 2D-CNN. In addition, the video data features are extracted using a slowfast feature extractor. And the information contained in the audio and video data, which have different domains, are combined into one feature that contains all the information. Afterwards, emotion recognition is performed using the combined features. Lastly, we evaluate the conventional methods that how to combine results from models and how to vote two model's results and a method of unifying the domain through feature extraction, then combining the features and performing classification using a classifier.

• Journal of Korean Academy of Nursing
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• v.46 no.5
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• pp.630-641
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• 2016

Purpose: This study was designed to construct a model which explains drug misuse behaviors in community-dwelling older adults. Methods: The design of this research is a cross-sectional study using structure equation modeling. The hypothetical model consisted of two types of variables: the exogenous variables of health status, cognitive ability, and negative emotion, and the endogenous variables of number of drugs, and drug misuse behaviors. The data collection was conducted from September 2 to September 21, 2013 through self-report questionnaires. Participants were 320 community-dwelling adults over the age of 65 living in J city. Data were analyzed with SPSS 21.0 program and Amos 18.0 program. Results: The results of the model fitness analysis were satisfied. The predictor variables for the hypothetical model explained 62.3% of variance regarding drug misuse behaviors. Drug misuse behaviors were directly affected by health status, cognitive ability, negative emotion and number of drugs and indirectly affected by health status, and negative emotion through number of drugs. Conclusion: These findings indicate factors that should be used in developing effective nursing interventions for safe and proper drug use and the prevention of drug misuse behaviors in community-dwelling older adults.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.13-24
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• 2014

Mobile phone makers compete for market shares through domination in media advertisements. These include domination of advertisements (Ads) in TV and the internet. However, the abundance and complexity of the competitions of Ads in TV does not guarantee advertising success which can influence consumers' emotion and the purchase intention towards the brand. This research analyses the case of a directional model on Attitude-towards-the-Ad model as a baseline into a new proposed correlation models (MacKenzie, Scott, &Lutz, 1989). The survey targets the involvements of Asian smartphone owners' attitude on advertisements, brands and purchase intentions. CFA (Confirmatory factor Analysis) was used in the research experiments, including hypothesis testing, the outcome of model fit which revealed significant levels and were successful. The study revealed that all three paths have consistently high coefficient paths (Attitude to Ads - Attitude to Brands - Purchase Intention), showing significant value of (${\beta}$=>.80), which supported each correlation factors. Therefore, this structural model, could set standards for creative managers and advertising teams to improve the brands visibility and build strong influences on attitudes in advertisements and improve purchase intentions.

• Human Ecology Research
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• v.55 no.6
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• pp.609-623
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• 2017

Fur apparel is a representative luxury item that displays wealth and social status; however, it is also recognized as an unethical product criticized for its animal maltreatment in the production process. Understanding consumer responses to an ambivalent object, such as fur apparel, is an important research topic both academically and practically. This study investigates the hierarchical effects of perceived benefits and risks of fur apparel on consumers' emotions and purchase intention by applying the ABC model of attitudes to identify the mediating effects of consumer emotions. An online survey was conducted on 390 female consumers that verified hypotheses through structural equation modeling and bootstrapping analysis using phantom variables. The initial results of the survey showed that the relationship between perceived conspicuous benefits and purchase intention towards fur apparel was partially mediated by positive emotion. Second, the relationship between perceived epistemic benefits and purchase intention was completely mediated by positive emotion. Third, the relationship between perceived ethical risk and purchase intention was completely mediated by positive and negative emotions. Fourth, perceived social risk did not affect the purchase intention of fur apparel significantly. The results support that cognitive beliefs about the subject have a significant positive effect on behavioral intentions through emotions as suggested in the ABC model of the attitude. This study provides an in-depth understanding of consumer responses to ambivalent objects by revealing the individual mediating effects of consumers' positive and negative emotions.

• Smart Media Journal
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• v.13 no.3
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• pp.9-17
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• 2024

Due to the recent pandemic and the development of ICT technology, the use of non-face-to-face and unmanned systems is expanding, and it is very important to understand emotions in communication in non-face-to-face situations. As emotion recognition methods for various facial expressions are required to understand emotions, artificial intelligence-based research is being conducted to improve facial expression emotion recognition in image data. However, existing research on facial expression emotion recognition requires high computing power and a lot of learning time because it utilizes a large amount of data to improve accuracy. To improve these limitations, this paper proposes a method of recognizing facial expressions using age and gender, which are image meta information, as a method of recognizing facial expressions with even a small amount of data. For facial expression emotion recognition, a face was detected using the Yolo Face model from the original image data, and age and gender were classified through the VGG model based on image meta information, and then seven emotions were recognized using the EfficientNet model. The accuracy of the proposed data classification learning model was higher as a result of comparing the meta-information-based data classification model with the model trained with all data.

• Journal of the Korean Society of Clothing and Textiles
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• v.40 no.2
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• pp.258-272
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• 2016

This study estimated a structural model for examining causal relationships among flagship store experiences, store emotion and loyalty, and to compare the structural models between luxury and fast fashion SPA brands. A total of 416 responses were collected from consumers who had experience with a variety of luxury and SPA flagship stores. Findings confirmed that flagship store experience consisted of four factors, such as sensory, affective, intellectual and behavioral experiences. Sensory and behavioral experiences had positive effects on store emotion that influenced loyalty. Affective and cognitive experiences influenced loyalty. All aspects of experiences explained store emotion or loyalty for luxury flagship stores; however, two of experiences (i.e., sensory and affective) were important to determine store emotion or loyalty for SPA flagship stores. The study discussed managerial implications for fashion brands to develop and manage flagship stores.

• Fashion & Textile Research Journal
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• v.11 no.3
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• pp.417-426
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• 2009

This study is to examine the structural relationships among store choice attributes, consumption emotion, relationship quality, and loyalty of Outlet. The data were collected from customers who have purchased clothing at the fashion outlet stores, For data analysis and structural equation model were analyzed by using LISREL. The subjects were male/female consumer experienced in purchasing clothes at fashion outlet stores. The results of this study are as follows: First, product, advertising, and instore atmostphere had significantly positive effect on consumption emotion. Second, consumption emotion had significantly positive effect on relationship quality(consumer's satisfaction and trust) and loyalty. Third, relationship quality(consumer's satisfaction and trust) had significantly positive effect on loyalty.

• Child Studies in Asia-Pacific Contexts
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• v.5 no.1
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• pp.1-19
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• 2015

Reintegration after military deployment is a significant family stressor. Guided by Eisenberg's heuristic model of socialization of emotions, the present study examined the relationships between parental emotion socialization, children's emotionality and children's internalizing symptoms using a military sample. It was also investigated whether gender of parents and children impacted parental emotion socialization. Questionnaires were gathered from 248 families with a 4-12 year old child (M = 7.78) in which a parent had been deployed to Iraq or Afghanistan. Children's emotionality was positively correlated with children's internalizing symptoms and non-supportive parental emotion socialization. Independent-t-tests and two-way ANOVAs showed that mothers reported more supportive reactions towards children's negative emotions than fathers. Father reports of expressive encouragement were positively associated with child reports of anxiety and depression. Child gender did not influence how parents responded to negative emotions. Implications and future directions were discussed.