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  • Open Access

    ARTICLE

    CNN-Based Voice Emotion Classification Model for Risk Detection

    Hyun Yoo1, Ji-Won Baek2, Kyungyong Chung3,*

    Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 319-334, 2021, DOI:10.32604/iasc.2021.018115

    Abstract With the convergence and development of the Internet of things (IoT) and artificial intelligence, closed-circuit television, wearable devices, and artificial neural networks have been combined and applied to crime prevention and follow-up measures against crimes. However, these IoT devices have various limitations based on the physical environment and face the fundamental problem of privacy violations. In this study, voice data are collected and emotions are classified based on an acoustic sensor that is free of privacy violations and is not sensitive to changes in external environments, to overcome these limitations. For the classification of emotions in the voice, the data… More >

  • Open Access

    ARTICLE

    Emotional Analysis of Arabic Saudi Dialect Tweets Using a Supervised Learning Approach

    Abeer A. AlFutamani, Heyam H. Al-Baity*

    Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 89-109, 2021, DOI:10.32604/iasc.2021.016555

    Abstract Social media sites produce a large amount of data and offer a highly competitive advantage for companies when they can benefit from and address data, as data provides a deeper understanding of clients and their needs. This understanding of clients helps in effectively making the correct decisions within the company, based on data obtained from social media websites. Thus, sentiment analysis has become a key tool for understanding that data. Sentiment analysis is a research area that focuses on analyzing people’s emotions and opinions to identify the polarity (e.g., positive or negative) of a given text. Since we need to… More >

  • Open Access

    ARTICLE

    Influence of Cultural Alienation on Happiness of Overseas Students: Mediating Role of Stress Relief and Regulating Role of Cultural Intelligence

    Xiaoxia Zhu1,2,*, Xu Guo2, Yishu Teng1,*, 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 >

  • Open Access

    ARTICLE

    Emotion Analysis: Bimodal Fusion of Facial Expressions and EEG

    Huiping Jiang1,*, 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 >

  • Open Access

    ARTICLE

    Higher Child-Reported Internalizing and Parent-Reported Externalizing Behaviors were Associated with Decreased Quality of Life among Pediatric Cardiac Patients Independent of Diagnosis: A Cross-Sectional Mixed-Methods Assessment

    Jacqueline S. Lee1,2, Angelica Blais1,2, Julia Jackson1, Bhavika J. Patel1, Lillian Lai4, Gary Goldfield1,3, Renee Sananes5, Patricia E. Longmuir1,2,3,*

    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 >

  • Open Access

    ARTICLE

    EP-Bot: Empathetic Chatbot Using Auto-Growing Knowledge Graph

    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 >

  • Open Access

    ARTICLE

    1D-CNN: Speech Emotion Recognition System Using a Stacked Network with Dilated CNN Features

    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 >

  • Open Access

    ARTICLE

    Emotional and Behavioral Problems of Left-Behind Children in Impoverished Rural China: A Comparative Cross-Sectional Study of First Grade Junior High School

    Yuming Zhou1, Chunxia Zhao2, Fan He1, Xiaobo Tian2, Yi Zheng1,*, Jing Sun3,*

    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 >

  • Open Access

    ARTICLE

    Affective State Recognition Using Thermal-Based Imaging: A Survey

    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 >

  • Open Access

    ARTICLE

    Image-Based Lifelogging: User Emotion Perspective

    Junghyun Bum1, Hyunseung Choo1, Joyce Jiyoung Whang2,*

    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 >

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