A. Saranya^1,*, R. Anandan²

Intelligent Automation & Soft Computing, Vol.33, No.2, pp. 1167-1182, 2022, DOI:10.32604/iasc.2022.023445

Abstract Hereditary Autism Spectrum Disorder (ASD) is a neuron disorder that affects a person's ability for communication, interaction, and also behaviors. Diagnostics of autism are available throughout all stages of life, from infancy through adolescence and adulthood. Facial Emotions detection is considered to be the most parameter for the detection of Autismdisorders among the different categories of people. Propelled with a machine and deep learning algorithms, detection of autism disorder using facial emotions has reached a new dimension and has even been considered as the precautionary warning system for caregivers. Since Facial emotions are limited to only seven expressions, detection of… More >

Ting Li^1,3,*, Qiang Xie^2,3

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 263-276, 2022, DOI:10.32604/ijmhp.2022.019177

Abstract COVID-19 has changed the way of learning and life of college students. The purpose is to explore the relationship between perceived stress and anxiety, and the mediating effect of resilience and regulatory emotional self-efficacy in college students during COVID-19. 309 students from three colleges were selected as research participants (average age 19.79 ± 1.11 years). SPSS was used to measure the correlation between variables. Amos was used to test the path coefficient and mediating effect of the hypothetical model. The results show that: Firstly, perceived stress has a significantly and positively predictive effect on anxiety. Secondly, psychological resilience and regulatory emotional self-efficacy… More >

Kuei-Feng Chang¹, Wen-Goang Yang², Ya-Wen Cheng³, I-Tung Shih^2,*

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 219-236, 2022, DOI:10.32604/ijmhp.2022.018187

Abstract This study explored the mechanism on how volunteers as rationalists use rationalism during their cognitive appraisal process when dealing with emotional events in their social helping behavior such as international rescue events. The authors used the triangulation method to include three studies (Study 1 is a qualitative research which explored ways of TCF leader’s inspiring their volunteer workers; Study 2 is a quantitative research on the decision-making process of volunteer individuals involving in international rescue activities; Study 3 is a quantitative research on individuals’ motivation for joining social helping behavior) for validation of Tzu Chi Foundation (TCF), which is a… More >

Muhammad Adnan Khan^1,2, Sagheer Abbas³, Ali Raza³, Faheem Khan⁴, T. Whangbo^4,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5911-5931, 2022, DOI:10.32604/cmc.2022.023557

Abstract Progress in understanding multisensory integration in human have suggested researchers that the integration may result into the enhancement or depression of incoming signals. It is evident based on different psychological and behavioral experiments that stimuli coming from different perceptual modalities at the same time or from the same place, the signal having more strength under the influence of emotions effects the response accordingly. Current research in multisensory integration has not studied the effect of emotions despite its significance and natural influence in multisensory enhancement or depression. Therefore, there is a need to integrate the emotional state of the agent with… More >

Louise Freeland¹, Michelle O’Reilly², Juliana Fleury³, Sarah Adams⁴, Panos Vostanis^1,*

International Journal of Mental Health Promotion, Vol.24, No.1, pp. 51-67, 2022, DOI:10.32604/ijmhp.2022.015706

Abstract Social emotional literacy (SEL) interventions are widely implemented through schools, with growing evidence for a range of positive child outcomes. Increasingly, such interventions are delivered on online platforms. To date, there is limited evidence about digital SEL interventions in low- and middle-income countries (LMIC). The aim of this study was to explore the perceptions and experiences of children, parents and facilitator of the potential value of addressing SEL via tailored digital intervention. The intervention was designed to help children, in Brazil, to cope during the first COVID-19 pandemic lockdown. The intervention was delivered via a digital platform to groups of… More >

Chih-Fang Huang^1,*, Cheng-Yuan Huang²

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1939-1953, 2022, DOI:10.32604/iasc.2022.017559

Abstract Musical emotion is important for the listener’s cognition. A smooth emotional expression generated through listening to music makes driving a car safer. Music has become more diverse and prolific with rapid technological developments. However, the cost of music production remains very high. At present, because the cost of music creation and the playing copyright are still very expensive, the music that needs to be listened to while driving can be executed by the way of automated composition of AI to achieve the purpose of driving safety and convenience. To address this problem, automated AI music composition has gradually gained attention… More >

Sung Park^1,*, Seongeon Park², Mincheol Whang²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3761-3784, 2022, DOI:10.32604/cmc.2022.023738

Abstract Artificial entities, such as virtual agents, have become more pervasive. Their long-term presence among humans requires the virtual agent's ability to express appropriate emotions to elicit the necessary empathy from the users. Affective empathy involves behavioral mimicry, a synchronized co-movement between dyadic pairs. However, the characteristics of such synchrony between humans and virtual agents remain unclear in empathic interactions. Our study evaluates the participant's behavioral synchronization when a virtual agent exhibits an emotional expression congruent with the emotional context through facial expressions, behavioral gestures, and voice. Participants viewed an emotion-eliciting video stimulus (negative or positive) with a virtual agent. The… More >

Ahmed R. Abas¹, Ibrahim Elhenawy¹, Mahinda Zidan^2,*, Mahmoud Othman²

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2943-2961, 2022, DOI:10.32604/cmc.2022.021671

Abstract Due to the widespread usage of social media in our recent daily lifestyles, sentiment analysis becomes an important field in pattern recognition and Natural Language Processing (NLP). In this field, users’ feedback data on a specific issue are evaluated and analyzed. Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research. Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature. Emotions describe a state of mind of distinct behaviors, feelings, thoughts and experiences. The main objective of this paper is to… More >

Yun-Kyu Lee¹, Dong-Sung Pae², Dae-Ki Hong³, Myo-Taeg Lim¹, Tae-Koo Kang^4,*

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 657-673, 2022, DOI:10.32604/iasc.2022.020849

Abstract With the advancement of human-computer interaction and artificial intelligence, emotion recognition has received significant research attention. The most commonly used technique for emotion recognition is EEG, which is directly associated with the central nervous system and contains strong emotional features. However, there are some disadvantages to using EEG signals. They require high dimensionality, diverse and complex processing procedures which make real-time computation difficult. In addition, there are problems in data acquisition and interpretation due to body movement or reduced concentration of the experimenter. In this paper, we used photoplethysmography (PPG) and electromyography (EMG) to record signals. Firstly, we segmented the… More >

Loan Trinh Van¹, Quang H. Nguyen^1,*, Thuy Dao Thi Le²

Computer Systems Science and Engineering, Vol.41, No.3, pp. 1083-1098, 2022, DOI:10.32604/csse.2022.021635

Abstract For human-machine communication to be as effective as human-to-human communication, research on speech emotion recognition is essential. Among the models and the classifiers used to recognize emotions, neural networks appear to be promising due to the network’s ability to learn and the diversity in configuration. Following the convolutional neural network, a capsule neural network (CapsNet) with inputs and outputs that are not scalar quantities but vectors allows the network to determine the part-whole relationships that are specific 6 for an object. This paper performs speech emotion recognition based on CapsNet. The corpora for speech emotion recognition have been augmented by… More >