Search results for: emotion regulation strategies

Authors: Jia-Ru Li, Ching-Wen Lin

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The study was designed to develop a measurement of the positive emotion regulation questionnaire (PERQ) that assesses positive emotion regulation strategies through self-report. The 14 items developed for the surveying instrument of the study were based upon literatures regarding elements of positive regulation strategies. 319 elementary students (age ranging from 12 to14) were recruited among three public elementary schools to survey on their use of positive emotion regulation strategies. Of 319 subjects, 20 invalid questionnaire s yielded a response rate of 92%. The data collected wasanalyzed through methods such as item analysis, factor analysis, and structural equation models. In reference to the results from item analysis, the formal survey instrument was reduced to 11 items. A principal axis factor analysis with varimax was performed on responses, resulting in a 2-factor equation (savoring strategy and neutralizing strategy), which accounted for 55.5% of the total variance. Then, the two-factor structure of scale was also identified by structural equation models. Finally, the reliability coefficients of the two factors were Cronbach-s α .92 and .74. Gender difference was only found in savoring strategy. In conclusion, the positive emotion regulation strategies questionnaire offers a brief, internally consistent, and valid self-report measure for understanding the emotional regulation strategies of children that may be useful to researchers and applied professionals.

Keywords: Emotional regulation, emotional regulation strategies, scale, SEM.

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Authors: Natalia Constantinescu

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This cross-sectional study aims to explore the differences among adults with somatic symptom disorder (SSD) versus adults without SSD, in terms of attachment and emotion regulation strategies. A total sample of 80 participants (40 people with SSD and 40 healthy controls), aged 20-57 years old (M = 31.69, SD = 10.55), were recruited from institutions and online groups. They completed the Romanian version of the Experiences in Close Relationships Scale – Short Form (ECR-S), Regulation of Emotion Systems Survey (RESS), Patient Health Questionnaire-15 (PHQ-15) and Somatic Symptom Disorder – B Criteria Scale (SSD-12). The results indicate significant differences between the two groups in terms of attachment and emotion regulation strategies. Adults with SSD have a higher level of attachment anxiety and avoidance compared to the nonclinical group. Moreover, people with SSD are more prone to use rumination and suppression and less prone to use reevaluation compared to healthy people. Implications for SSD prevention and treatment are discussed.

Keywords: adult attachment, emotion regulation strategies, psychosomatic disorders, somatic symptom disorder

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Authors: AKM Rezaul Karim, Tania Sharafat, Abu Yusuf Mahmud

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The study aimed to investigate whether cognitive emotion regulation in children varies with parenting style, family type and gender. Toward this end, cognitive emotion regulation and perceived parenting style of 206 school children were measured. Standard regression analyses of data revealed that the models were significant and explained 17.3% of the variance in adaptive emotion regulation (Adjusted R²=0.173; F=9.579, p<.001), and 7.1% of the variance in less adaptive emotion regulation (Adjusted R²=.071, F=4.135, p=.001). Results showed that children’s cognitive emotion regulation is functionally associated with parenting style, but not with family type and their gender. Amongst three types of parenting, authoritative parenting was the strongest predictor of the overall adaptive emotion regulation while authoritarian parenting was the strongest predictor of the overall less adaptive emotion regulation. Permissive parenting has impact neither on adaptive nor on less adaptive emotion regulation. The findings would have important implications for parents, caregivers, child psychologists, and other professionals working with children or adolescents.

Keywords: Cognitive Emotion Regulation, Adaptive, Less Adaptive, Parenting Style, Family Type.

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Authors: Eduardo da Silva, Tânia Caetano, Jessica B. Lopes

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Emotion dysregulation has been linked to psychopathology in general and, in particular, to substance abuse and other addiction-related disorders, such as eating disorders, impulsive disorder, and gambling. It has been proposed that a lessening of the difficulties in emotion regulation can have a significant positive impact on the treatment of these disorders. The present study explores the association between the progress in the Change & Grow^® therapeutic model (5 stages of treatment), and the decrease in the difficulties related to emotion regulation. The Change & Grow^® model has five stages of treatment according to the model’s five principles (Truth, Acceptance, Gratitude, Love and Responsibility) and incorporates different therapeutic approaches such as positive psychology, cognitive and behavioral therapy and third generation therapies. The main objective is to understand the impact of the presented therapeutic model on difficulties in emotion regulation in patients with addiction-related disorders. The exploratory study has a cross-sectional design. Participants were 44 (15 women and 29 men) Portuguese patients in the residential Villa Ramadas International Treatment Centre. The instrument used was the Portuguese version of the Difficulties in Emotion Regulation Scale (DERS), which measures six dimensions of emotion regulation (Strategies, Non-acceptance, Awareness, Impulse, Goals, and Clarity). The mean rank scores for both the DERS total score and the Impulse subscale showed statistically significant differences according to Stage of Treatment/Principles. Furthermore, Stage of Treatment/Principles held a negative correlation with the scores of the Non-acceptance and Impulse subscales, as well as the DERS total score. The results indicate that the Change & Grow^® model seems to have an impact in lessening the patient’s difficulties in emotion regulation. The Impulse dimension suffered the greater impact, which supports the well-known relevance of impulse control, or related difficulties, in addiction-related disorders.

Keywords: Addiction, Change & Grow®, emotion regulation, psychopathology.

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Authors: Junseok Ham, Chansun Jung, Junhyung Park, Jihye Ryeo, Ilju Ko

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It is hard to express emotion through only speech when we watch a character in a movie or a play because we cannot estimate the size, kind, and quantity of emotion. So this paper proposes an artificial emotion model for visualizing current emotion with color and location in emotion model. The artificial emotion model is designed considering causality of generated emotion, difference of personality, difference of continual emotional stimulus, and co-relation of various emotions. This paper supposed the Emotion Field for visualizing current emotion with location, and current emotion is expressed by location and color in the Emotion Field. For visualizing changes within current emotion, the artificial emotion model is adjusted to characters in Hamlet.

Keywords: Emotion, Artificial Emotion, Visualizing, EmotionModel.

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Authors: Jia-Ru Li, Chia-Jung Li, Ching-Wen Lin

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Contrary to negative emotion regulation, coping with positive moods have received less attention in adolescent adjustment. However, some research has found that everyone is different on dealing with their positive emotions, which affects their adaptation and well-being. The purpose of the present study was to investigate the relationship between positive emotions dampening and internalizing behavior problems of adolescent in Taiwan. A survey was conducted and 208 students (12 to14 years old) completed the strengths and difficulties questionnaire (SDQ), the Affect Intensity Measure, and the positive emotions dampening scale. Analysis methods such as descriptive statistics, t-test, Pearson correlations and multiple regression were adapted. The results were as follows: Emotionality and internalizing problem behavior have significant gender differences. Compared to boys, girls have a higher score on negative emotionality and are at a higher risk for internalizing symptoms. However, there are no gender differences on positive emotion dampening. Additionally, in the circumstance that negative emotionality acted as the control variable, positive emotion dampening strategy was (positive) related to internalizing behavior problems. Given the results of this study, it is suggested that coaching deconstructive positive emotion strategies is to assist adolescents with internalizing behavior problems is encouraged.

Keywords: Emotion dampening strategies, internalizing problem behaviors, affect intensity.

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Authors: Jia-Ru Li, Chih-Hung Wang, Ching-Wen Lin

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Internet addiction has become a critical problem on adolescents in Taiwan, and its negative effects on various dimensions of adolescent development caught the attention of educational and psychological experts. This study examined the correlation between cognitive (locus of control) and emotion (emotion venting strategies) factors on internet addiction of adolescents in Taiwan. Using the Compulsive Internet Use (CIU) and the Emotion Venting Strategy scales, a survey was conducted and 215 effective samples (students ranging from12 to14 years old) returned. Quantitative analysis methods such as descriptive statistics, t-test, ANOVA, Pearson correlations and multiple regression were adopted. The results were as follows: 1. Severity of Internet addiction has significant gender differences; boys were at a higher risk than girls in becoming addicted to the Internet. 2. Emotion venting, locus of control and internet addiction have been shown to be positive correlated with one another. 3. Setting the locus of control as the control variable, emotion venting strategy has positive and significant contribution to internet addiction. The results of this study suggest that coaching deconstructive emotion strategies and cognitive believes are encouraged to integrate with actual field work.

Keywords: Emotion venting strategy, locus of control, adolescent internet addiction.

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Authors: Jia-Ru Li, Chih-Hung Wang, Ching-Wen Lin

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The association between emotional inhibition strategies linked to depression has been showed inconsistent among studies. Mild emotional inhibition maybe benefit for social interaction, especially for female among East Asian cultures. The present study aimed to examine whether the inhibition–depression relationship is dependent on level of emotion inhibition and gender context, given differing value of suppressing emotional displays. We hypothesized that the negative associations between inhibition and adolescent depression would not directly, in which affected by interaction between emotion inhibition and gender. To test this hypothesis, we asked 309 junior high school students which age range from 12 to14 years old to report on their use of emotion inhibition and depression syndrome. A multiple regressions analysis revealed that significant interaction that gender as a moderator to the relationships between emotion inhibition and adolescent depression. The group with the highest level of depression was girls with high levels of emotion inhibition, whose depression score was higher than that of boys with high levels of emotion inhibition. The result highlights that the importance of context in understanding the inhibition-depression relationship.

Keywords: Emotional inhibition strategies, gender, adolescent depression.

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Authors: Latifeh PourMohammadBagher

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In this paper I have developed a system for evaluating the degree of fear emotion that the intelligent agent-based system may feel when it encounters to a persecuting event. In this paper I want to describe behaviors of emotional agents using human behavior in terms of the way their emotional states evolve over time. I have implemented a fuzzy inference system using Java environment. As the inputs of this system, I have considered three parameters related on human fear emotion. The system outputs can be used in agent decision making process or choosing a person for team working systems by combination the intensity of fear to other emotion intensities.

Keywords: Emotion simulation, Fear, Fuzzy intelligent agent

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Authors: Musbah M. Aqel, P. K. Mahanti, Soumya Banerjee

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This paper describes a simulation model for analyzing artificial emotion injected to design the game characters. Most of the game storyboard is interactive in nature and the virtual characters of the game are equipped with an individual personality and dynamic emotion value which is similar to real life emotion and behavior. The uncertainty in real expression, mood and behavior is also exhibited in game paradigm and this is focused in the present paper through a fuzzy logic based agent and storyboard. Subsequently, a pheromone distribution or labeling is presented mimicking the behavior of social insects.

Keywords: Artificial Emotion, Fuzzy logic, Game character, Pheromone label

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Authors: Nouha Khediri, Mohammed Ben Ammar, Monji Kherallah

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Recently, facial emotion recognition (FER) has become increasingly essential to understand the state of the human mind. However, accurately classifying emotion from the face is a challenging task. In this paper, we present a facial emotion recognition approach named CV-FER benefiting from deep learning, especially CNN and VGG16. First, the data are pre-processed with data cleaning and data rotation. Then, we augment the data and proceed to our FER model, which contains five convolutions layers and five pooling layers. Finally, a softmax classifier is used in the output layer to recognize emotions. Based on the above contents, this paper reviews the works of facial emotion recognition based on deep learning. Experiments show that our model outperforms the other methods using the same FER2013 database and yields a recognition rate of 92%. We also put forward some suggestions for future work.

Keywords: CNN, deep-learning, facial emotion recognition, machine learning.

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Authors: Vesna Kirandziska, Nevena Ackovska, Ana Madevska Bogdanova

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The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.

Keywords: Emotion recognition, facial recognition, signal processing, machine learning.

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Authors: I. Abasi, L. Fata, M. Sadeghi, S. Banihashemi, A. Mohammadee

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Background: Dimensional and transdiagnostic approaches as a result of high comorbidity among mental disorders have captured researchers and clinicians interests for exploring the latent factors to development and maintenance of some psychological disorders. The goal of present study is comparing some of these common factors between generalized anxiety disorder and unipolar mood disorder. Methods: 27 patients with generalized anxiety disorder, 29 patients with depression disorder were recruited by using SCID-I and 69 non-clinical populations were selected by using GHQ cut off point. MANCOVA was used for analyzing data. Results: The results show that worry, rumination, intolerance of uncertainty, maladaptive metacognitive beliefs, and experiential avoidance were all significantly different between GAD and unipolar mood disorder groups. However, there weren’t any significant differences in difficulties in emotion regulation and neuroticism between GAD and unipolar mood disorder groups. Discussion: Results indicate that although there are some transdiagnostic and common factors in GAD and unipolar mood disorder, there may be some specific vulnerability factors for each disorder. Further study is needed for answering these questions.

Keywords: Depression, emotion regulation, generalized anxiety disorder, transdiagnostic.

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Authors: Hirohide Ushida

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This paper discusses an artificial mind model and its applications. The mind model is based on some theories which assert that emotion is an important function in human decision making. An artificial mind model with emotion is built, and the model is applied to action selection of autonomous agents. In three examples, the agents interact with humans and their environments. The examples show the proposed model effectively work in both virtual agents and real robots.

Keywords: Artificial mind, emotion, interactive agent, pet robot

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Authors: Simin Sadeghi-Saeb

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Metacognitive strategies consistently play important roles in reading comprehension. The metacognitive strategies involve the active monitoring and consequent regulation and orchestration of the cognitive processes in relation to the cognitive objects or data on which they bear. In this paper, the effect of instruction in using metacognitive strategies on reading academic materials, type of metacognitive strategies were mostly used by college university students before and after the instruction and the level they use those strategies before and after the instruction were studied. For these aims, 50 female college students were chosen. Then, they were divided randomly into two groups, experimental and control groups. At first session, students in both groups took the standard TOFEL exam. After the pre-test had been administered, the instruction began. After treatment, a post-test was taken. It is useful to state that after pre-test and post-test the same questionnaire was handed to the students of experimental group. The results of this research show that the instruction of metacognitive strategies has positive effect on the students' scores in reading comprehension tests. Furthermore, it showed that before and after the instruction, the students' usage of metacognitive strategies changed. Also, it demonstrated that the instruction affected the students' level of metacognitive strategies' usage.

Keywords: EFL students, English reading comprehension, instruction, metacognitive strategies.

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Authors: Robert Niese, Ayoub Al-Hamadi, Bernd Michaelis

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In modern human computer interaction systems (HCI), emotion recognition is becoming an imperative characteristic. The quest for effective and reliable emotion recognition in HCI has resulted in a need for better face detection, feature extraction and classification. In this paper we present results of feature space analysis after briefly explaining our fully automatic vision based emotion recognition method. We demonstrate the compactness of the feature space and show how the 2d/3d based method achieves superior features for the purpose of emotion classification. Also it is exposed that through feature normalization a widely person independent feature space is created. As a consequence, the classifier architecture has only a minor influence on the classification result. This is particularly elucidated with the help of confusion matrices. For this purpose advanced classification algorithms, such as Support Vector Machines and Artificial Neural Networks are employed, as well as the simple k- Nearest Neighbor classifier.

Keywords: Facial expression analysis, Feature extraction, Image processing, Pattern Recognition, Application.

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Authors: S. Ali, R. Yunus, A. Arif, Y. Ayaz, M. Baber Sial, R. Asif, N. Naseer, M. Jawad Khan

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In this study, we have proposed a gesture to emotion recognition method using flex sensors mounted on metacarpophalangeal joints. The flex sensors are fixed in a wearable glove. The data from the glove are sent to PC using Wi-Fi. Four gestures: finger pointing, thumbs up, fist open and fist close are performed by five subjects. Each gesture is categorized into sad, happy, and excited class based on the velocity and acceleration of the hand gesture. Seventeen inspectors observed the emotions and hand gestures of the five subjects. The emotional state based on the investigators assessment and acquired movement speed data is compared. Overall, we achieved 77% accurate results. Therefore, the proposed design can be used for emotional state detection applications.

Keywords: Emotion identification, emotion models, gesture recognition, user perception.

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: Public emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining.

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Authors: Vadivel Ayyasamy

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The present approach deals with the identification of Emotions and classification of Emotional patterns at Phrase-level with respect to Positive and Negative Orientation. The proposed approach considers emotion triggered terms, its co-occurrence terms and also associated sentences for recognizing emotions. The proposed approach uses Part of Speech Tagging and Emotion Actifiers for classification. Here sentence patterns are broken into phrases and Neuro-Fuzzy model is used to classify which results in 16 patterns of emotional phrases. Suitable intensities are assigned for capturing the degree of emotion contents that exist in semantics of patterns. These emotional phrases are assigned weights which supports in deciding the Positive and Negative Orientation of emotions. The approach uses web documents for experimental purpose and the proposed classification approach performs well and achieves good F-Scores.

Keywords: Emotions, sentences, phrases, classification, patterns, fuzzy, positive orientation, negative orientation.

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Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari

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People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.

Keywords: Body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech.

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Authors: P. Visutsak

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The study of the interaction between humans and computers has been emerging during the last few years. This interaction will be more powerful if computers are able to perceive and respond to human nonverbal communication such as emotions. In this study, we present the image-based approach to emotion classification through lower facial expression. We employ a set of feature points in the lower face image according to the particular face model used and consider their motion across each emotive expression of images. The vector of displacements of all feature points input to the Adaptive Support Vector Machines (A-SVMs) classifier that classify it into seven basic emotions scheme, namely neutral, angry, disgust, fear, happy, sad and surprise. The system was tested on the Japanese Female Facial Expression (JAFFE) dataset of frontal view facial expressions [7]. Our experiments on emotion classification through lower facial expressions demonstrate the robustness of Adaptive SVM classifier and verify the high efficiency of our approach.

Keywords: emotion classification, facial expression, adaptive support vector machines, facial expression classifier.

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Authors: Tugce Ercan

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This research study aims to identify the impact of two factors –growth and competitive strategies- on a set of building production innovation strategies. It was conducted a questionery survey to collect data from construction professionals and it was asked them the importance level of predicted innovation strategies for corporate strategies. Multiple analysis of variance (MANOVA) was employed to see the main and interaction effects of corporate strategies on building innovation strategies. The results indicate that growth strategies such as entering in a new a market or new project types has a greater effect on innovation strategies rather than competitive strategies such as cost leadership or differentiation strategies. However the interaction effect of competitive strategies and growth strategies on innovation strategies is much bigger than the only effect of competitive strategies. It was also analyzed the descriptive statistics of innovation strategies for different competitive and growth strategy types.

Keywords: competitive strategy, growth strategy, innovation, construction company, MANOVA

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Authors: Yungeng Xie, Cong Liu, Yi Liu, Xuanao Wan

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The study aims to explore microblog users’ emotion expression and sharing behaviors on the Chinese microblog (Weibo). The first theme of study analyzed whether microblog emotions impact readers’ message sharing behaviors, specifically, how the strength of emotion (positive and negative) in microblog messages facilitate/inhibit readers’ sharing behaviors. The second theme compared the differences among the three types of microblog users (i.e., verified enterprise users, verified individual users and unverified users) in terms of their profiles and microblog behaviors. A total of 7114 microblog messages about 24 hot public events in China were sampled from Sina Weibo. The first study results show that strength of negative emotions that microblog messages carry significantly increase the possibility of the message being shared. The second study results indicate that there are significant differences across the three types of users in terms of their emotion expression and its influence on microblog behaviors.

Keywords: Microblog, emotion expression, information diffusion.

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Authors: Suprijanto, Linda Sari, Vebi Nadhira , IGN. Merthayasa. Farida I.M

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Detection of human emotions has many potential applications. One of application is to quantify attentiveness audience in order evaluate acoustic quality in concern hall. The subjective audio preference that based on from audience is used. To obtain fairness evaluation of acoustic quality, the research proposed system for multimodal emotion detection; one modality based on brain signals that measured using electroencephalogram (EEG) and the second modality is sequences of facial images. In the experiment, an audio signal was customized which consist of normal and disorder sounds. Furthermore, an audio signal was played in order to stimulate positive/negative emotion feedback of volunteers. EEG signal from temporal lobes, i.e. T3 and T4 was used to measured brain response and sequence of facial image was used to monitoring facial expression during volunteer hearing audio signal. On EEG signal, feature was extracted from change information in brain wave, particularly in alpha and beta wave. Feature of facial expression was extracted based on analysis of motion images. We implement an advance optical flow method to detect the most active facial muscle form normal to other emotion expression that represented in vector flow maps. The reduce problem on detection of emotion state, vector flow maps are transformed into compass mapping that represents major directions and velocities of facial movement. The results showed that the power of beta wave is increasing when disorder sound stimulation was given, however for each volunteer was giving different emotion feedback. Based on features derived from facial face images, an optical flow compass mapping was promising to use as additional information to make decision about emotion feedback.

Keywords: Multimodal Emotion Detection, EEG, Facial Image, Optical Flow, compass mapping, Brain Wave

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Authors: Arthur Yan

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Recent theorizations on the cognitive process of moral judgment have focused on the role of intuitions and emotions, marking a departure from previous emphasis on conscious, step-by-step reasoning. My study investigated how being in a disgusted mood state affects moral judgment. Participants were induced to enter a disgusted mood state through listening to disgusting sounds and reading disgusting descriptions. Results shows that they, when compared to control who have not been induced to feel disgust, are more likely to endorse actions that are emotionally aversive but maximizes utilitarian return The result is analyzed using the 'emotion-as-information' approach to decision making. The result is consistent with the view that emotions play an important role in determining moral judgment.

Keywords: Disgust, mood induction, moral judgment, emotion-as-information.

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Authors: M. de Miguel Molina, V. Santamarina Campos, M. V. Segarra Oña, B. de Miguel Molina

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Safety and security concerns play a key role during the design of civil UAs (aircraft controlled by a pilot who is not onboard it) by the producers and the offer of different services by the operators. At present, European countries have fragmented regulations about the manufacture and use of civil drones, therefore the European institutions are trying to approach all these regulations into a common one. In this sense, not only law but also ethics can give guidelines to the industry in order to obtain better reports from their clients. With our results, we would like to give advice to the European industry, as well as give new insights to the academia and policymakers.

Keywords: Ethics, regulation, safety, security.

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Authors: Shakirat Abimbola Adesola, Shuaib Akintunde Asifat, Jelili Olalekan Amoo

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This paper presented the impact of students’ emotions on learning when receiving lectures and when taking tests. It was observed during the study that students experience different types of emotions, and this was found to have a significant effect on their academic performance. A total of 1675 students from the department of Computer Science in two Colleges of Education in South-West Nigeria took part in this study. The students were randomly selected for the research. The sample comprises of 968 males representing 58%, and 707 females representing 42%. A structured questionnaire, of Motivated Strategies for Learning Questionnaire (MSLQ) was distributed to the participants to obtain their opinions. Data gathered were analyzed using the IBM SPSS 20 to obtain ANOVA, descriptive analysis, stepwise regression, and reliability tests. The results revealed that emotion moderately shape students’ motivation and engagement in learning; and that self-regulation and self-determination do have significant impact on academic performance. It was further revealed that test anxiety has a significant correlation with academic performance.

Keywords: Motivation, self-determination, test anxiety, academic performance, academic engagement.

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Authors: Chaiyut Sumpavakup, Thanatchai Kulworawanichpong

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This paper presents the voltage regulation scheme of D-STATCOM under three-phase faults. It consists of the voltage detection and voltage regulation schemes in the 0dq reference. The proposed control strategy uses the proportional controller in which the proportional gain, kp, is appropriately adjusted by using genetic algorithms. To verify its use, a simplified 4-bus test system is situated by assuming a three-phase fault at bus 4. As a result, the DSTATCOM can resume the load voltage to the desired level within 1.8 ms. This confirms that the proposed voltage regulation scheme performs well under three-phase fault events.

Keywords: D-STATCOM, proportional controller, genetic algorithms.

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Authors: Najwa Alsayed Omar

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With the increasing popularity of the Internet, online reading has become an essential source for EFL readers. Using strategies to comprehend information on online reading texts play a crucial role in students’ academic success. Metacognitive reading strategies are effective factors that enhance EFL learners reading comprehension. This study aimed at exploring the use of online metacognitive reading strategies by postgraduate Libyan EFL students. Quantitative data was collected using the Survey of Online Reading Strategies (OSORS). The findings revealed that the participants were moderate users of metacognitive online reading strategies. Problem solving strategies were the most frequently reported used strategies, while support reading strategies were the least. The five most and least frequently reported strategies were identified. Based on the findings, some future research recommendations were presented.

Keywords: Metacognitive strategies, Online reading, Online reading strategies, Postgraduate students.

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: Emotion detection, TF-IDF, WEKA tool, classification algorithms.

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