• Land and Housing Review
• /
• v.2 no.4
• /
• pp.315-324
• /
• 2011

In the merged organization, the efforts of integration such as various PMI activities, etc. are exerted and the performance of PMI can be judged by evaluating the effectiveness of an organization. In this paper, the empirical analysis was conducted to see what effects of 'planned PMI activities' and 'voluntary integration efforts' have on the effectiveness of an organization which is 'Organizational Commitment', 'Job Satisfaction', 'Emotional Integration' and 'Shared Value Recognition'. The survey was made on the employees of LH, which is a representative case of public corporation advancement, and SPSS 17.0 and AMOS 17 were used for the analysis. As a result of the analysis of a structural equation model, it indicated that both 'planned PMI activities' and 'voluntary integration efforts' have direct influence on 4 indices of effectiveness of an organization respectively. In particular, it was found that 'planned PMI activities' affects 'Shared Value Recognition' the most and 'voluntary integration efforts' has the largest effect on 'Emotional Integration'. Through this study, it was verified that voluntary integration efforts of members as well as the planed formal PMI activities are also very important factor of effect on the integration performance of an organization.

• Journal of the Korean Home Economics Association
• /
• v.40 no.7
• /
• pp.25-40
• /
• 2002

The purpose of this study was to examine the relationships between child's emotional intelligence and stress according to child's sex. The subjects for this study were 380 children of 5-6th grade selected from elementary schools in Busan. Kwak's questionnaires(1994) on child's emotional intelligence and Han, Mi-Hyun's questionnaires(1996) on child's stress were used. Statistical techniques such as Manoya, Pearson's correlation, canonical were used. The results were as follows : (1) According to sex, there were significant differences in child's emotional intelligence and stress. The girls showed higher emotional expression, emotional empathy, emotional control, and the friend-related stress than boys. The boys showed higher parent-related stress than girls. (2) There were significant negative correlations between child's emotional intelligence and stress. The children who got higher emotion intelligence perceived lower stress. (3) Among five dimensions of emotional intelligence for boy, the effective variable was emotional utilization. And among six dimensions of stress, the effective variables were home-environment stress and school-related stress. Among fine dimensions of emotional intelligence for girl, the effective variables were emotional expression and emotional recognition. And among six dimensions of stress, the effective variables were friend-related stress and parent-related stress.

• Journal of Families and Better Life
• /
• v.31 no.3
• /
• pp.49-62
• /
• 2013

The purpose of this study was to investigate the emotional ability between abused children and general children by comparing their emotional intelligence and emotional control. Participants were 17 abused children who had been separated from their abusers and 17 general children, all elementary school students. The answers to the questionnaire items on emotional intelligence and situations of emotional motivation were analyzed by Mann-Whitney U as a study tool. The results of this study were as follows: First, the difference of emotional intelligence between abused children and general children was statistically significant. Abused children received lower scores than general children when it came to their emotional recognition, emotional expression, empathy, and emotional regulation as a subordinate scope of emotional intelligence. Second, the difference of emotional regulation strategy between abused children and general children was statistically significant. Abused children presented negative responses and less frequently used positive strategy, inhibitory avoidance strategy and alternative strategy than general children. Third, the difference of emotional regulation motivation between abused children and general children was statistically significant. Abused children presented less prosocial motivation, motivation of self-preservation and normative motivation than general children.

• Korean Journal of Child Studies
• /
• v.25 no.6
• /
• pp.171-189
• /
• 2004

Children develop emotional intelligence during the early years of life, and according to experts, emotional intelligence(EI) is a more reliable predictor of academic achievement than IQ. However, nowadays children appear to be low on emotional well-being. This has potentially negative consequences, not only for academic achievement but also for personal relationships. The purpose of this study was to develop emotional education program for young children(EEPYC). In this study, EI is defined to carry out reasoning in regard to emotions and to use emotion for enhancement of thought. Designed to facilitate development of young children's EI. EEPYC is based on the four branch model, which is mental EI model and based on the guiding principle of Collaborative to Advance Social and Emotional Learning. The subgroups(curricular) that compose EEPYC are Emotional Perception, appraisal, and expression, Self-recognition program, Self-esteem program, Emotional Stress Regulation, Emotional problem solving & conflict resolution. EEPYC has the potential of fostering emotional intelligence. Moreover, EEPYC can promote a motivation, prosocial activity, and regulation of stress. This helps young children to develope cognition and emotion in harmonious fashion.

• Korean Institute of Interior Design Journal
• /
• v.16 no.2 s.61
• /
• pp.139-146
• /
• 2007

This study is tended to analyze the characteristics of the emotional office environment so that digital technologies may adapt to the rapidly progressing social structure in a flexible way, investigate the interior composition of the changing office space and the element and direction of design and then present the indoor environment appropriate to it with the desirable alternative to the emotional office. The recognition of emotionality becomes so important that it is called 'emotional society'. Emotional design, which is mostly concern about user's consensus & experiences and in the space, is appeared on office. Emotional design is understanded from a interactive point of view, human and interior-space. The important factors of this study are light, color, immateriality and fun sensitivity The purpose of this study is to examine the emotional design by analysis of multifarious spaces. Office space Is designed emotional and experienced in the future.

• International journal of advanced smart convergence
• /
• v.4 no.2
• /
• pp.154-162
• /
• 2015

This paper focuses on how cognitive and emotional structures affect humans during long-term interaction. We design an interaction with a turn-based game, the Chopstick Game, in which two agents play with numbers using their fingers. While a human and a robot agent alternate turn, the human user applies herself to play the game and to learn new winning skills from the robot agent. Conventional valence and arousal space is applied to design emotional interaction. For the robotic system, we implement finger gesture recognition and emotional behaviors that are designed for three-dimensional virtual robot. In the experimental tests, the properness of the proposed schemes is verified and the effect of the emotional interaction is discussed.

• Science of Emotion and Sensibility
• /
• v.21 no.4
• /
• pp.77-90
• /
• 2018

Behavioral studies of emotion recognition in autism spectrum disorders (ASD) have yielded mixed results. Most of the studies focused on emotion recognition abilities with regard to ASD using stimuli with unisensory modality, making it difficult to determine difficulties in real life emotion perception in ASD. Herein, we review the recent behavioral and cognitive neuroscience studies on emotion recognition functions in ASD, including both unisensory and multisensory emotional information, to elucidate the possible difficulties in emotion recognition in ASD. In our study, we discovered that people with ASD have problems in the process of integrating emotional information during emotion recognition tasks. The following four points are discussed: (1) The restrictions of previous studies, (2) deficits in emotion recognition in ASD especially in recognizing multisensory information, (3) possible compensation mechanisms for emotion recognition in ASD, and (4) the possible roles of attention and language functions in emotion recognition in ASD. The compensatory mechanisms proposed herein for ASD with regard to emotion recognition abilities could contribute to a therapeutic approach for improving emotion recognition functions in ASD.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.681-686
• /
• 2012

This paper studied the speech parameters less affected by the human emotion for the development of the robust emotional speech recognition system. For this purpose, the effect of emotion on the speech recognition system and robust speech parameters of speech recognition system were studied using speech database containing various emotions. In this study, mel-cepstral coefficient, delta-cepstral coefficient, RASTA mel-cepstral coefficient, root-cepstral coefficient, PLP coefficient and frequency warped mel-cepstral coefficient in the vocal tract length normalization method were used as feature parameters. And CMS (Cepstral Mean Subtraction) and SBR(Signal Bias Removal) method were used as a signal bias removal technique. Experimental results showed that the HMM based speaker independent word recognizer using frequency warped RASTA mel-cepstral coefficient in the vocal tract length normalized method, its derivatives and CMS as a signal bias removal showed the best performance.

• Journal of Internet Computing and Services
• /
• v.24 no.2
• /
• pp.11-18
• /
• 2023

Recently, in the field of Speech Emotion Recognition (SER), many studies have been conducted to improve accuracy using voice features and modeling. In addition to modeling studies to improve the accuracy of existing voice emotion recognition, various studies using voice features are being conducted. This paper, voice files are separated by time interval in a time series method, focusing on the fact that voice emotions are related to time flow. After voice file separation, we propose a model for classifying emotions of speech data by extracting speech features Mel, Chroma, zero-crossing rate (ZCR), root mean square (RMS), and mel-frequency cepstrum coefficients (MFCC) and applying them to a recurrent neural network model used for sequential data processing. As proposed method, voice features were extracted from all files using 'librosa' library and applied to neural network models. The experimental method compared and analyzed the performance of models of recurrent neural network (RNN), long short-term memory (LSTM) and gated recurrent unit (GRU) using the Interactive emotional dyadic motion capture Interactive Emotional Dyadic Motion Capture (IEMOCAP) english dataset.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2000.04a
• /
• pp.366-369
• /
• 2000

This paper examines three algorithms to recognize speaker's emotion using the speech signals. Target emotions are happiness, sadness, anger, fear, boredom and neutral state. MLB(Maximum-Likeligood Bayes), NN(Nearest Neighbor) and HMM (Hidden Markov Model) algorithms are used as the pattern matching techniques. In all cases, pitch and energy are used as the features. The feature vectors for MLB and NN are composed of pitch mean, pitch standard deviation, energy mean, energy standard deviation, etc. For HMM, vectors of delta pitch with delta-delta pitch and delta energy with delta-delta energy are used. We recorded a corpus of emotional speech data and performed the subjective evaluation for the data. The subjective recognition result was 56% and was compared with the classifiers' recognition rates. MLB, NN, and HMM classifiers achieved recognition rates of 68.9%, 69.3% and 89.1% respectively, for the speaker dependent, and context-independent classification.