Xiaoxia Zhu^1,2,*, Xu Guo², Yishu Teng^1,*, John Gershenson³

International Journal of Mental Health Promotion, Vol.23, No.2, pp. 289-302, 2021, DOI:10.32604/IJMHP.2021.013691

Abstract When the global outbreak of new coronary pneumonia broke out in 2020, online public opinion events triggered by cultural differences among overseas students had come into the public view. To further explore the relationship between the cultural alienation of overseas students and their own happiness, this study takes visualization and analysis of positive, negative sentiment analysis of Weibo netizens’ comment data in the “Xu Kexin Incident” as the starting point, on the basis of introducing cultural alienation, stress relief methods, and cultural intelligence, combining gender and social ability, social relations and other individual attributes, designed a questionnaire to investigate 502… More >

Huiping Jiang^1,*, Rui Jiao¹, Demeng Wu¹, Wenbo Wu²

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2315-2327, 2021, DOI:10.32604/cmc.2021.016832

Abstract With the rapid development of deep learning and artificial intelligence, affective computing, as a branch field, has attracted increasing research attention. Human emotions are diverse and are directly expressed via non-physiological indicators, such as electroencephalogram (EEG) signals. However, whether emotion-based or EEG-based, these remain single-modes of emotion recognition. Multi-mode fusion emotion recognition can improve accuracy by utilizing feature diversity and correlation. Therefore, three different models have been established: the single-mode-based EEG-long and short-term memory (LSTM) model, the Facial-LSTM model based on facial expressions processing EEG data, and the multi-mode LSTM-convolutional neural network (CNN) model that combines expressions and EEG. Their… More >

Jacqueline S. Lee^1,2, Angelica Blais^1,2, Julia Jackson¹, Bhavika J. Patel¹, Lillian Lai⁴, Gary Goldfield^1,3, Renee Sananes⁵, Patricia E. Longmuir^1,2,3,*

Congenital Heart Disease, Vol.16, No.3, pp. 255-267, 2021, DOI:10.32604/CHD.2021.014628

Abstract Background: Pediatric cardiology patients often experience decreased quality of life (QoL) and higher rates of mental illness, particularly with severe disease, but the relationship between them and comparisons across diagnostic groups are limited. This mixed-methods cross-sectional study assessed the association between QoL anxiety and behavior problems among children with structural heart disease, arrhythmia, or other cardiac diagnoses. Methods: Children (6–14 years, n = 76, 50% female) and their parents completed measures of QoL (PedsQL), behavior (BASC-2, subset of 19 children) and anxiety (MASC-2, children 8+ years). Pearson correlations/regression models examined associations between QoL, behavior and anxiety, controlling for age, sex,… More >

SoYeop Yoo, OkRan Jeong^*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2807-2817, 2021, DOI:10.32604/cmc.2021.015634

Abstract People occasionally interact with each other through conversation. In particular, we communicate through dialogue and exchange emotions and information from it. Emotions are essential characteristics of natural language. Conversational artificial intelligence is an integral part of all the technologies that allow computers to communicate like humans. For a computer to interact like a human being, it must understand the emotions inherent in the conversation and generate the appropriate responses. However, existing dialogue systems focus only on improving the quality of understanding natural language or generating natural language, excluding emotions. We propose a chatbot based on emotion, which is an essential… More >

Mustaqeem, Soonil Kwon^*

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 4039-4059, 2021, DOI:10.32604/cmc.2021.015070

Abstract Emotion recognition from speech data is an active and emerging area of research that plays an important role in numerous applications, such as robotics, virtual reality, behavior assessments, and emergency call centers. Recently, researchers have developed many techniques in this field in order to ensure an improvement in the accuracy by utilizing several deep learning approaches, but the recognition rate is still not convincing. Our main aim is to develop a new technique that increases the recognition rate with reasonable cost computations. In this paper, we suggested a new technique, which is a one-dimensional dilated convolutional neural network (1D-DCNN) for… More >

Yuming Zhou¹, Chunxia Zhao², Fan He¹, Xiaobo Tian², Yi Zheng^1,*, Jing Sun^3,*

International Journal of Mental Health Promotion, Vol.23, No.1, pp. 1-13, 2021, DOI:10.32604/IJMHP.2020.013093

Abstract Objective: To investigate the prevalence of emotional and behavioral problems and related factors of left-behind children in impoverished rural China (mainly in the first grade of junior high school). Methods: A cross-sectional survey of rural households in 27 poverty-stricken counties in 12 provinces across China was conducted using the Strengths and Difficulties Questionnaire (SDQ). Results: The prevalence of emotional and behavioral problems in left-behind children was 11.7%, and that of non-left-behind children was 8.9%. There was statistical difference between the two groups (P < 0.01). There are no differences between the two groups in terms of the various factors of… More >

Mustafa M. M. Al Qudah, Ahmad S. A. Mohamed^*, Syaheerah L. Lutfi

Computer Systems Science and Engineering, Vol.37, No.1, pp. 47-62, 2021, DOI:10.32604/csse.2021.015222

Abstract The thermal-based imaging technique has recently attracted the attention of researchers who are interested in the recognition of human affects due to its ability to measure the facial transient temperature, which is correlated with human affects and robustness against illumination changes. Therefore, studies have increasingly used the thermal imaging as a potential and supplemental solution to overcome the challenges of visual (RGB) imaging, such as the variation of light conditions and revealing original human affect. Moreover, the thermal-based imaging has shown promising results in the detection of psychophysiological signals, such as pulse rate and respiration rate in a contactless and… More >

Junghyun Bum¹, Hyunseung Choo¹, Joyce Jiyoung Whang^2,*

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1963-1977, 2021, DOI:10.32604/cmc.2021.014931

Abstract Lifelog is a digital record of an individual’s daily life. It collects, records, and archives a large amount of unstructured data; therefore, techniques are required to organize and summarize those data for easy retrieval. Lifelogging has been utilized for diverse applications including healthcare, self-tracking, and entertainment, among others. With regard to the image-based lifelogging, even though most users prefer to present photos with facial expressions that allow us to infer their emotions, there have been few studies on lifelogging techniques that focus upon users’ emotions. In this paper, we develop a system that extracts users’ own photos from their smartphones… More >

Lianne M. Geerdink^1,2,*, Malindi van der Mheen^3,4, Gideon J. du Marchie Sarvaas⁵, Irene M. Kuipers⁶, Stefan Frerich⁷, Henriëtte ter Heide², Willem A. Helbing⁸, Zina Feijzic¹, Christian Schroer⁹, Chris L. de Korte¹⁰, Livia Kapusta^1,11, Chris M. Verhaak¹², Elisabeth M. W. J. Utens^3,4

Congenital Heart Disease, Vol.15, No.6, pp. 457-472, 2020, DOI:10.32604/CHD.2020.012994

Abstract Background: Due to the improved survival rates of children and adolescents with congenital heart disease (CHD), more attention is now being directed towards their health-related quality of life (HRQoL), emotional and behavioral problems. Ebstein anomaly (EA) is a rare CHD with a broad clinical spectrum. The aim of the current study is to evaluate self- and proxy-reported HRQoL and emotional and behavioral problems in children and adolescents with EA. Methods: In this cross-sectional, multicenter study, we included EA patients (aged 8–17 years), who underwent routine clinical assessments in Dutch university hospitals between May 2017 and March 2019. The Generic Pediatric… More >

Xinxin Lu^1,*, Hong Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 281-297, 2020, DOI:10.32604/cmes.2020.010948

Abstract As an interdisciplinary comprehensive subject involving multidisciplinary knowledge, emotional analysis has become a hot topic in psychology, health medicine and computer science. It has a high comprehensive and practical application value. Emotion research based on the social network is a relatively new topic in the field of psychology and medical health research. The text emotion analysis of college students also has an important research significance for the emotional state of students at a certain time or a certain period, so as to understand their normal state, abnormal state and the reason of state change from the information they wrote. In… More >