The Impact of Decentralized Technologies on Social Media Megacorporations

Social media is a mega-industry built by systematically monetizing the exploitation of human emotions, reactions, and biases. The authors explain how this industry became so profitable by creating a fear of missing out (FOMO) to command our attention, blending news and content in one feed to keep users 'in-app', and using powerful algorithms to promote more provocative posts, filter content, and trigger the reward centres of our brains. The authors examine how decentralized technologies, including cryptocurrencies, tokenization, and blockchain are being developed and deployed into new social media applications. The authors speculate on how these blockchain-backed startups could challenge the status quo and appeal to new expectations of user privacy, tighter regulation, and a more equitable monetization system.

Application of Gamification in a Marketing Context

Gamification, a popular tool widely used in various contexts such as marketing, education, and organizations, among others, has demonstrated its potential for engaging, motivating, and achieving behavioral change in the targeted audience. For an ideal gamification system, it is necessary to know how the gamification elements affect human emotions. This chapter conducts a journey through gamified contexts and their psychological impacts on individuals. This chapter gathers up the different threads of gamification in the marketing context. The three important objectives fulfilled by this chapter would be that it provides information about the topic of gamification and the psychological perspectives behind its operation; discusses its application in various marketing contexts, such as digital marketing and online payment sites; and finally, investigates various behavioral outcomes of gamification.

Global-local attention for emotion recognition

Human emotion recognition is an active research area in artificial intelligence and has made substantial progress over the past few years. Many recent works mainly focus on facial regions to infer human affection, while the surrounding context information is not effectively utilized. In this paper, we proposed a new deep network to effectively recognize human emotions using a novel global-local attention mechanism. Our network is designed to extract features from both facial and context regions independently, then learn them together using the attention module. In this way, both the facial and contextual information is used to infer human emotions, therefore enhancing the discrimination of the classifier. The intensive experiments show that our method surpasses the current state-of-the-art methods on recent emotion datasets by a fair margin. Qualitatively, our global-local attention module can extract more meaningful attention maps than previous methods. The source code and trained model of our network are available at https://github.com/minhnhatvt/glamor-net.

Effect of Coriander Plants on Human Emotions, Brain Electrophysiology, and Salivary Secretion

Coriander is a popular herb with versatile applications. However, the current research about coriander medicinal values have been mainly focusing on its extracts while lacking in the relationship between living coriander plants and emotion. Therefore, this study aims to investigate the effects of coriander plants on human emotions and physiological activities. The results showed that the main Volatile organic compounds (VOCs) of coriander plants were 2-ethyl-1-hexanol, d-limonene, eucalyptol, benzyl alcohol, Isophorone, dimethyl glutarate, α-terpineol, styrene, methyl methacrylate, α-pinene. Coriander plants could significantly reduce the angry sub-scores, alpha amylase and amino acids (arginine, proline, histidine, and taurine) concentrations in saliva. Theta (4–8 Hz) band activity of the cerebral cortex was significantly enhanced. Moreover, taurine significantly positively correlated with anger and negatively correlated with vigor. All the results signified that coriander plant could influence the activity of brain electrophysiological and salivary secretion through its VOCs to improve people’s negative emotions.

Art and its relevance in the emotional well-being of people

Art, considered in its manifestations, whether through music, singing, painting, dancing, and all the possible expressions it can have, is undoubtedly a beautiful way to enrich the soul, the spirit, and human emotions. In this work, the different forms of understanding art, and the benefits that it can have on people, are exposed. It that art in its multiple manifestations can help control stress, anxiety, and depression. For this purpose, the investigators use bibliographic support to compare academic scenarios, artistic expressions that allow people to improve their emotional, physical, and psychological health. For this purpose, is implemented a bibliographic search to comparing academic scenarios, artistic manifestations that allow people to improve their emotional, physical, and psychological health. On the other hand, it was possible to verify that music performed as a half-hour therapy helps children with catastrophic illnesses, relieving pain. Keywords: art, human emotions, artistic expressions. References [1]E. Panosfky and F. Saxl, MITOLOGÍA CLÁSICA EN EL ARTE MEDIEVAL, Áurea, 2021. [2]A. Casanova, «Arteterapia: A arte como instrumento no trabalho do psicólogo,» Psicologia, Ciéncia e Profissao, vol. 34, nº 1, pp. 142-157, 2014. [3]A. Ballesta, O. Vizcaino and E. Mesas, «El arte como un lenguaje posible en las personas con capacidades diversas, » Arte y Políticas de indentidad, vol. 4, nº junio, pp. 137-152, 2011. [4]C. López, «El arte como forma de realidad, » [Online]. Available: https://d1wqtxts1xzle7.cloudfront.net/64011688/Herbert%20Marcuse%20-%20El%20arte%20como%20forma%20de%20realidad-with-cover-page-v2.pdf?Expires=1629957713&Signature=RnZvL4~kWoJF5i0g-BZySz2YpCZgiTsQrx3khQFL80iZznlDRONCJBRLMFEaNDMoAvyVlP~mafoZFAsQfIU5y3d-bJy7. [Last access: August 27, 2021]. [5]E. Hernández-pacheco, «Comisión de investigaciones paleontológicas y prehistóricas,» Junta para ampliación de estudios e investigaciones científicas, Madrid, 2018. [6]Himmelman, «Lo bucólico en el arte antiguo,» de Instituto Arqueológico Alemán, Madrid, 1973. [7]J. Cervelló, Escritura, lengua y cultura en el antiguo egipto, Barcelona: Universidad autónoma de Barcelona, 2015. [8]P. Bosh-Gimpera, «El arte rupestre en América,» Anales de antropología, vol. 1, nº 1, 1964. [9]V. Córdoba, «La música en la edad media,» [Online]. Available: https://www.timetoast.com/timelines/musica-de-la-edad-media. [Last access: August 28, 2021] [10]Pinterest, «Los instrumentos del renacimiento, » [Online]. Available: https://www.pinterest.com/pin/247698048233408250/. [Last access: August 28, 2021] [11]almomento.mx, «El cambio de la música a la época barroca,» 12 marzo 2021. [Online]. Available: https://almomento.mx/historia-de-la-musica-barroca/. [Last access: August 28, 2021] [12]Pinterest, «Música clásica para estudiar y relajarse, » [Online]. Available: https://www.pinterest.es/pin/355221489342463596/. [Last access: August 28, 2021] [13]F. Suárez and L. Rosales, La ingeniería de las emociones humanas, Quito: AutanaBooks, 2021. [14]F. Suárez, L. Rosales y Á. Lezama, Computación inteligente y estados emocionales, Quito: AutanaBooks, 2020. [15]J. Morey, «Intervención plástica como soporte emocional para niños en el instituto nacional de salud del niño-Hospital del Niño,» Hospital del Niño, 2017. [16]J. P. S. De la Rubia y C. Cabañéz, «Impacto fisiológico de la musicoterapia en la depresión, ansiedad, y bienestar del paciente con demencia tipo Alzheimer. Valoración de la utilización de cuestionarios para cuantificarlo, » European Journal of Investigation in Health, vol. 4, nº 2, pp. 131-140, 2014. [17]J. Tresierra, «Musicoterapia y pediatría,» Revista peruana de pediatría, pp. 53-55, 2005. [18]E. Torres-Ake, G. Lugo-Ake, J. Matos-Villanueva and E. Socorro, «Masaje frente a musicoterapia para reducir el estrés en prematuros de una unidad crítica neonatal, una revisión sistemática,» Rev. Enferm Inst Mex Seguro Soc., vol. 28, nº 1, pp. 49-57, 2020.

The Makna Denotasi dan Makna Konotasi Dalam Film Animasi “Amirotur Ruum” Karya Hadi Mohammadian: Semiotika Roland Barthes

This article aims to describe the meaning of denotation and connotation in the animated film Amīrat al-Rūm by Hadi Mohammadian using the semiotic theory of Roland Barthes. Barthes explained that in the meaning of the word, there are two parts, denotation, namely the original meaning contained in the dictionary, and connotation, where this meaning involves human emotions and thoughts. This type of research is descriptive qualitative research, and the data source used is the animated film Amīrat al-Rūm by Hadi Mohammadian. The data collection technique uses watching, listening, and translating. Meanwhile, the data analysis is linguistic messages, unencoded iconic messages, and encoded iconic messages. The results of this study indicate that in the animated film Amīrat al-Rūm many dialogues contain denotative and connotative meanings.

Effective Technique for Noise Removal and Emotion Recognition in Speech Signals Using Cat Swarm Optimized Spiking Neural Networks

Speech processing is one of the required fields in digital signal processing that helps in processing the speech signals. The speech process is utilized in different fields such as emotion recognition, virtual assistants, voice identification, etc. Among the various applications, emotion recognition is one of the critical areas because it is used to recognize people’s exact emotions and eliminate physiological issues. Several researchers utilize signal processing and machine learning techniques together to find the exact human emotions. However, they fail to attain their feelings with less computational complexity and high accuracy. This paper introduces the intelligent computational technique called cat swarm optimized spiking neural network (CSSPNN). Initially, the emotional speech signal is collected from the Toronto emotional speech set (TESS) dataset, which is then processed by applying a wavelet approach to extract the features. The derived features are further examined using the defined classifier CSSPNN, which recognizes human emotions due to the effective training and learning process. Finally, the proficiency of the system is determined using experimental results and discussions. The proposed system recognizes the speech emotions up to 99.3% accuracy compared to recurrent neural networks (RNNs), deep neural networks (DNNs) and deep shallow neural networks (DSNNs).