In recent years, Intelligent Personal Assistants (IPAs) have emerged as important tools in human–computer interaction, with a wide range of applications such as voice assistant, virtual customer ...service, and navigation. Capturing and understanding the prominent emotional needs of users is important for improving the quality of service of IPAs. Multimodal emotion recognition in conversation (MMERC) aimed at automatically identifying and tracking the emotional states of speakers during the dialogue process has become a crucial component for building emotional IPAs and attracted increasing attention. Current research in this field is based on graph simulation for cross-modal and single-modal interactions. However, these methods ignore the highly imbalanced class problem inherent in MMERC, leading to a decrease in the generalization ability of the model and an inability to effectively recognize minority emotion classes. Data mining methods use oversampling to solve the imbalanced classification, but they are unsuitable for MMERC as they disrupt the conversational coherence and modality alignment characteristics of multimodal emotion recognition datasets. To overcome these problems, this paper proposes an IMBA-MMERC, which is an effective framework to address the pervasive issue of class imbalance in MMERC. Within this framework, sample generation for multimodal conversation tackles the application challenges that exist in multimodal conversational emotion recognition datasets, and well-classified encouraging loss mitigates the performance degradation of the model on certain majority classes due to decision boundary deviations. On two English benchmark datasets and one Chinese public dataset, we used two performance indicators to demonstrate the effectiveness and superiority of the proposed IMBA-MMERC. Ablation experiment, case study, and histograms visualization further verify the well performance of the proposed framework.
Extension professionals can benefit from knowing the value of a program’s outcomes compared to how much it costs. One way to estimate a program’s value relative to cost is through a series of ...calculations, known as Return on Investment (ROI). This 4-page fact sheet describes ROI and how Extension professionals can use it in their programming. Written by Amanda D. Ali, Laura A. Warner, and Hayk Khachatryan, and published by the Department of Agricultural Education and Communication, December 2016. AEC608/WC270: Estimating Return on Investment (ROI) for a Behavior Change: An Evaluation Tool for Extension Programs (ufl.edu)
An object can be consisting of various attributes, such as illuminance, appearance, shape, orientation, etc. Separately extract these attributes has enormous value in visual effects modeling, ...attribute-specific retrieval and recognition. Essentially, these attributes can be fairly abstract and thus need labels to extract. However, sometimes the labels of these attributes may not be available with training data. A solution to this problem is projecting the observed data into a lower dimension latent subspace, such that each observed data can be represented by a latent variable. After that, the dimensions of a latent variable can be segmented into different parts by weighting the kernel automatic relevance determination (ARD) parameters. Consequently, the latent variable is segmented into different parts each of which corresponds to the main attribute. In real life scenery, the attributes of an object may vary significantly from case to case. For instance, a single face can probably be under different illuminance conditions. Taking into account the diversity of these attribute variations, we propose the Diversified Shared Latent Variable Model (DSLVM) to extract and manipulate object attributes in an unsupervised way. More specifically, we initially set up two views that share the same latent variables. Then, two Diversity Encouraging (DE) priors are applied to the inducing points of each model view. Here, the inducing points are a small representative dataset that explains the observed data in its entirety. Meanwhile, the exploited diversity encouraging priors are able to cover more diverse characteristics of the attributes. The defined objective function is computed by variational inference. Extensive experiments on different datasets demonstrate that our method can accurately deal with various object.
Today, dealers, institutions and service providers need to attract customers to their product with effective advertisements. The commercials then play an important role for selling and effectively ...attracting customers. The language tools help to encourage customers to purchase goods. Jakobson- linguist and founder of the Prague school- enumerated six roles for language, one of which is the conative role. According to this view, it is possible to distinguish three types of conative roles: encouraging, descriptive and threatening. In the present study, 100 cases of frequently encountered commercials were reviewed. The findings of the study indicated that the encouraging conative role (47%) was used more frequently than descriptive conative (46%) and threatening conative (7%) roles
Due to its comprehensiveness and extreme complexity, the phenomenon of creativity has always attracted the attention of researchers, but only with the rapid development of science, technique, and ...technology, more intensive studies of this phenomenon began in the early 1990s. The importance of creativity is pointed out by numerous theorists, emphasizing the importance of this phenomenon on an individual, social and global level. Creativity plays a major role in creating individual meaningful works that contribute to wider social progress. The rapid progress of science and technology requires new and unusual reactions, and consequently, modern society is looking for young inspiring, talented, inspired, creative and innovative people who will be able to respond to the challenges they face every day. Education plays a key role in preparing them for life in modern society, but critics of modern education question the role of the school in encouraging and developing creativity. On the one hand, the school is an institution that cultivates creativity and creative activities, but on the other hand, as many say, the school kills and suffocates everything that young people would have and could show. This paper discusses the concept of creativity, as well as the role of education, school, and teachers in encouraging and awakening creativity in young people. The analysis of relevant and recent pedagogical literature seeks to answer the question of whether and in what way the school is limiting the development of creativity, what are the obstacles and blockers of creativity in school, and how to eliminate them.
This study aims to highlight aspects of mutual protection and encouragement of investments between Algeria and Tunisia in accordance with the Agreement for the Promotion and Protection of Investments ...signed between them, in order to create the appropriate Conditions to support economic cooperation between the two countries. We have concluded that the agreement gave guarantees that allow the investors of the two countries to invest in a good environment and climate. Among these guarantees are the guarantee of national treatment and the treatment of the Most Favoured Nation Treatment.
Implicit learning refers to the process of unconsciously learning complex knowledge through feedback. Previous studies investigated the influences of different types of feedback (e.g., social and ...non-social feedback) on implicit learning. This study focused on the social information presented in the learning situation and tried to explore the effects of different social feedback on implicit rule learning. We assigned participants randomly into an encouraging facial feedback group (happy expression for correct answer, neutral but not negative expression for incorrect answer) and a discouraging facial feedback group (neutral but not happy expression for correct answer, negative expression for incorrect answer). The implicit learning task included four difficulty levels, and social feedback was presented in the learning phase but not the testing phase in two experiments. The only difference between the two experiments was that the sad face used as negative feedback in Experiment 1 was replaced with an angry face in Experiment 2 to enhance the ecological validity of the discouraging facial feedback group. These two experiments yielded consistent results: the performances in the encouraging facial feedback group were more accurate in both the learning and the testing phases at all difficulty levels. These findings indicated that the influence of encouraging social feedback for a better implicit learning achievement was stable and established a new groundwork for future research on incentive-based education, making it critical to investigate the impact of various forms of encouraging-based education on learning.
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