• Title/Summary/Keyword: Emotion flow

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Deokhu: Differences of investment activity and flow level according to self-perception, emotional change before-after deokhu activity (덕후: 자기 지각에 따른 투자 활동과 몰입 수준 차이, 덕후 활동 전후의 정서 변화)

  • KIM, SU-SIE;Lee, Heung-Pyo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.1
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    • pp.75-84
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    • 2019
  • The purpose of this study was to investigate whether there is a difference between the deokhu activities and the flow level of the deokhu group. We also tested whether there are any real differences in emotion before and after the deokhu activities. The study included 227 adults and results were as follows. First, the deokhu group had a high cost of investing and a high rate of one-day investments, particularly for one-week activities and years of duration compare to the non-deokhu group. Second, the higher the degree to which they perceived themselves as deokhu and the level of deokhu activities were higher in flow. and the group of deokhu was more absorbed than the non-deokhu group. Third, there has been no change in positive and negative feelings before and after deokhu activities in the non-deokhu group. For the deokhu group, the positive emotions of happiness, joy, tranquility, pleasure increased and negative emotions such as anger, anxiety, sadness, shame, and guilt were significantly reduced after deokhu activities. The perception of deokhu and deokhu activities have positive functions that increase the level of flow, relieve negative feelings and enhance positive emotions.

A Study on Emotion Recognition of Chunk-Based Time Series Speech (청크 기반 시계열 음성의 감정 인식 연구)

  • Hyun-Sam Shin;Jun-Ki Hong;Sung-Chan Hong
    • Journal of Internet Computing and Services
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    • v.24 no.2
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    • pp.11-18
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    • 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.

Predictors of Subjective Happiness for Nursing Students (간호대학생의 주관적 행복감에 영향을 미치는 요인)

  • Jo, Geum-Yi;Park, Hyun-Sook
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.1
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    • pp.160-169
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    • 2011
  • The purposes of this study were to identify the significant predictors of subjective happiness for nursing students. The subjects consisted of 385 nursing students. Data were collected through self-report questionnaires, which were constructed to include positive emotion, gratitude disposition, flow, self-esteem, and subjective happiness. The data were analyzed by the PASW. 18.0 program. The significant predictors of subjective happiness for nursing students were gratitude disposition, self-esteem, flow, physical health status, positive emotion, and economic status, explaining 49.4% of the variance in subjective happiness. The most important predictors of subjective happiness for nursing students were gratitude disposition, self-esteem, and flow. The findings of this study suggest that the approach to effective happiness promotion program for nursing students should consider gratitude disposition, self-esteem, and flow.

Variation of facial temperature to 3D visual fatigue evoked (3D 시각피로 유발에 따른 안면 온도 변화)

  • Hwang, Sung Teac;Park, SangIn;Won, Myoung Ju;Whang, MinCheol
    • Science of Emotion and Sensibility
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    • v.16 no.4
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    • pp.509-516
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    • 2013
  • As the visual fatigue induced by 3D visual stimulation has raised some safety concerns in the industry, this study aims to quantify the visual fatigue through the means of measuring the facial temperature changes. Facial temperature was measured for one minute before and after watching a visual stimulus. Whether the visual fatigue has occurred was measured through subjective evaluations and high cognitive tasks. The difference in the changes that occurred after watching a 2D stimulus and a 3D stimulus was computed in order to associate the facial temperature changes and the visual fatigue induced by watching 3D contents. The results showed significant differences in the subjective evaluations and in the high cognitive tasks. Also, the ERP latency increased after watching 3D stimuli. There were significant differences in the maximum value of the temperature at the forehead and at the tip of the nose. A previous study showed that 3D visual fatigue activates the sympathetic nervous system. Activation of the sympathetic nervous system is known to increase the heart rate as well as the blood flow into the face through the carotid arteries system. When watching 2D or 3D stimuli, the sympathetic nervous system activation dictates the blood flow, which then influences the facial temperature. This study is meaningful in that it is one of the first investigations that looks into the possibility to measure 3D visual fatigue with thermal images.

A Study on Wearable Emotion Monitoring System Under Natural Conditions Applying Noncontact Type Inductive Sensor (자연 상태에서의 인간감성 평가를 위한 비접촉식 인덕티브 센싱 기반의 착용형 센서 연구)

  • Hyun-Seung Cho;Jin-Hee Yang;Sang-Yeob Lee;Jeong-Whan Lee;Joo-Hyeon Lee;Hoon Kim
    • Science of Emotion and Sensibility
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    • v.26 no.3
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    • pp.149-160
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    • 2023
  • This study develops a time-varying system-based noncontact fabric sensor that can measure cerebral blood-flow signals to explore the possibility of brain blood-signal detection and emotional evaluation. The textile sensor was implemented as a coil-type sensor by combining 30 silver threads of 40 deniers and then embroidering it with the computer machine. For the cerebral blood-flow measurement experiment, subjects were asked to attach a coil-type sensor to the carotid artery area, wear an electrocardiogram (ECG) electrode and a respiration (RSP) measurement belt. In addition, Doppler ultrasonography was performed using an ultrasonic diagnostic device to measure the speed of blood flow. The subject was asked to wear Meta Quest 2, measure the blood-flow change signal when viewing the manipulated image visual stimulus, and fill out an emotional-evaluation questionnaire. The measurement results show that the textile-sensor-measured signal also changes with a change in the blood-flow rate signal measured using the Doppler ultrasonography. These findings verify that the cerebral blood-flow signal can be measured using a coil-type textile sensor. In addition, the HRV extracted from ECG and PLL signals (textile sensor signals) are calculated and compared for emotional evaluation. The comparison results show that for the change in the ratio because of the activation of the sympathetic and parasympathetic nervous systems due to visual stimulation, the values calculated using the textile sensor and ECG signals tend to be similar. In conclusion, a the proposed time-varying system-based coil-type textile sensor can be used to study changes in the cerebral blood flow and monitor emotions.

An Influence through the Mediating of Flows Play about the Attraction and Emotions Absorption of the Website (웹사이트의 매력성과 고객의 정서적 몰입에 대한 플로우의 매개적 영향 - 인터넷 쇼핑몰에서의 의류구매행동을 중심으로 -)

  • Kang, Sung-Ju
    • International Commerce and Information Review
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    • v.10 no.2
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    • pp.63-87
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    • 2008
  • This study investigates the relationship between perceived system characteristics of Internet shopping mall and loyalty, and examines how perceived website attractiveness and flow play mediating roles between perceived system characteristics of Internet shopping mall and affective commitment in the context of Internet clothing shopping mall. For these purposes, the author developed a structural model which consists of several variables. In this model, perceived system characteristics of Internet shopping mall that consist of such as familiarity, reputation, uniqueness, positive emotion, self-efficacy, and interactivity were proposed to affect the website attractiveness and flow, and in turn, result in higher affective commitment. Thus, perceived website attractiveness and flow were proposed as core mediating variables between perceived mobile service characteristics and affective commitment. To test unidimensionality and nomological validity of the measures of each construct, the author employed scale refinement procedure. The results of reliability test with Cronbach's, and confirmatory factor analysis warranted unidimensionality of the measures for each construct. In addition, nomological validity of the measures was warranted from the result of correlation analysis.

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The Effects of the Attractiveness of an Internet Shopping Mall and Flow on Affective Commitment

  • Kang, Sung-Ju;Kim, Jae-Yeong;Park, Young-Kyun
    • Journal of Distribution Science
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    • v.9 no.4
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    • pp.29-42
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    • 2011
  • With the many advantages of the internet, online shopping has become one of the fastest growing types of retail businesses. However, internet-based firms are much more firmly required to retain existing customers rather than secure new ones, and to make them revisit the site by strengthening trust and loyalty, thereby improving profits and outrivaling competitors. Commitment is an essential part of successful long-term relationships between buyers and sellers. Although commitments by both parties in an exchange can provide the foundation for the development of relational social norms, disproportionate commitments can lead to opportunism by the less committed partner. Moreover, flow, which is characterized by intense concentration and enjoyment, was found to be significantly linked with exploratory use behavior, which in turn was linked to the extent of computer use. The level of flow was, itself, determined by the individual's sense of being in control, and the level of challenge perceived in maneuvering a website. Website attractiveness goes hand in hand with the attractiveness of an internet shopping mall, and it can be conceptualized as the persuasive effectiveness of a message by the use of familiarity, favor, similarity, etc. It occurs when information receivers try to achieve self-satisfaction when they actually or emotionally identify themselves with an information source. This study investigates the relationship between the perceived system characteristics of an internet shopping mall and the loyalty of online consumers, and it examines how perceived website attractiveness and flow play mediating roles between the perceived system characteristics of an internet shopping mall and the affective commitment in the context of a clothes internet shopping mall. For these purposes, a structural model comprising several variables was developed. That model was tested with an analysis of moment structure (AMOS) using data from respondents who had purchased clothing through the internet during the past three months. In this model, the perceived system characteristics of an internet shopping mall, such as familiarity, reputation, uniqueness, positive emotions, self-efficacy, and interactivity, were proposed to affect the website's attractiveness and flow, and lead to a higher affective commitment over time. Thus, the perceived website attractiveness and flow were proposed as core mediating variables between perceived system characteristics and affective commitment. The results of a reliability test using Cronbach's Alpha, and a confirmatory factor analysis warranted using unidimensionality for the measures for each construct. In addition, the nomological validity of the measures was warranted from the results of a correlation analysis. The results of empirical analyses indicated that systematic attributes resulting in website attractiveness and user's characteristics, thereby triggering customers' flow, play a crucial role in inducing customers' affective commitment, and a user's characteristics are twice as important as systematic attributes in this study. Moreover, familiarity, reputation, and uniqueness all have a significant effect on website attractiveness, and the research showed that uniqueness took the first place, and that familiarity and reputation followed in order of magnitude. The fact that reputation was not the most important factor that affects the attractiveness of an internet shopping mall, with uniqueness or familiarity having a greater impact, suggests much deeper implications. Finally, positive emotion, self-efficacy, and interactivity all have a significant effect on customers' flow. In particular, the fact that positive emotion, compared to self-efficacy or interactivity, has much more impact on flow is very suggestive.

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Effects of Brief Character Strength Workshop for Enhancement of Positivity (긍정성 증진을 위한 단기 성격 강점 워크샵의 효과)

  • Kim, Sun-Young;Lee, Ji-Eun;Choi, Jeong-Woo;Han, You;Beak, Kung-Hee;Huh, Hyu-Jung;Chae, Jeong-Ho
    • Anxiety and mood
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    • v.10 no.1
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    • pp.52-58
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    • 2014
  • Objective : The purpose of this study is to develop the one-session positive psychology based strength enhancing workshop and verify effect of this program. This program is composed of lecture based on positive psychology and activities for identifying and utilizing personal character strengths. Methods : Total 81 participants were participated in this study. Positive Resources Test was assessed the change of personal positive resources at pre-, post program and subjective satisfaction for the workshop was measured at the post program. Repeated-t test was performed to identify the effect of this program. Results : Among the positive resources, satisfaction with life, positive affect, gratitude, acceptance, personal growth, efficacy, flow, resilience, hope, spirituality are significantly increased after program. Conclusion : Although this study is a single-session program without control group for comparison, it is meaningful to try a short-term intervention concise the program consisting of more than 8 sessions. This study will be based on the future development a variety of positive interventions.

Communications of Emotions with Character Movements (캐릭터의 움직임을 통한 감성 커뮤니케이션)

  • Shim, Shin-Hae;Lee, Tae-Il;Cho, Sung-Hyun
    • Journal of Korea Game Society
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    • v.7 no.4
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    • pp.33-42
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    • 2007
  • Advanced technologies and techniques make it possible to express digital animation with higher quality. Characters in the virtual animation space are playing an important role in emphasizing the human audiences or interacting directly with them. The movement of characters gives them vital power, and shows their intentions and emotions. To analyze the emotion of character movements, the study develops basic movement sources based on Laban's property elements of movement such as time, space, and flow, and tries to find the relationship between their movements and the emotions they arouse by positioning them on Plutchik's emotional circle. We find that each element of 9 movements represent its own emotion consistently, and has influence on the intensity of emotions clearly.

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Emotion Classification DNN Model for Virtual Reality based 3D Space (가상현실 기반 3차원 공간에 대한 감정분류 딥러닝 모델)

  • Myung, Jee-Yeon;Jun, Han-Jong
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.36 no.4
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    • pp.41-49
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    • 2020
  • The purpose of this study was to investigate the use of the Deep Neural Networks(DNN) model to classify user's emotions, in particular Electroencephalography(EEG) toward Virtual-Reality(VR) based 3D design alternatives. Four different types of VR Space were constructed to measure a user's emotion and EEG was measured for each stimulus. In addition to the quantitative evaluation based on EEG data, a questionnaire was conducted to qualitatively check whether there is a difference between VR stimuli. As a result, there is a significant difference between plan types according to the normalized ranking method. Therefore, the value of the subjective questionnaire was used as labeling data and collected EEG data was used for a feature value in the DNN model. Google TensorFlow was used to build and train the model. The accuracy of the developed model was 98.9%, which is higher than in previous studies. This indicates that there is a possibility of VR and Fast Fourier Transform(FFT) processing would affect the accuracy of the model, which means that it is possible to classify a user's emotions toward VR based 3D design alternatives by measuring the EEG with this model.