Deep Learning Based Emotion Recognition and Visualization of Figural Representation

This exploration aims to study the emotion recognition of speech and graphic visualization of expressions of learners under the intelligent learning environment of the Internet. After comparing the performance of several neural network algorithms related to deep learning, an improved convolution neural network-Bi-directional Long Short-Term Memory (CNN-BiLSTM) algorithm is proposed, and a simulation experiment is conducted to verify the performance of this algorithm. The experimental results indicate that the Accuracy of CNN-BiLSTM algorithm reported here reaches 98.75%, which is at least 3.15% higher than that of other algorithms. Besides, the Recall is at least 7.13% higher than that of other algorithms, and the recognition rate is not less than 90%. Evidently, the improved CNN-BiLSTM algorithm can achieve good recognition results, and provide significant experimental reference for research on learners’ emotion recognition and graphic visualization of expressions in an intelligent learning environment.

Publications related to virtual laboratories during the covid 19 pandemic: A bibliometric review and analysis

During the COVID-19 pandemic, virtual laboratories are instrumental in learning physics concepts. A virtual laboratory is one media that can be used as a solution to carry out concept discovery activities through simulation using computer software. This article was created to explain the trend of publications related to virtual laboratories during the COVID-19 pandemic for 2020-2021 through bibliometric analysis of the literature. The papers analyzed were obtained using the Publish or Perish (PoP) software on the Google Scholar database. The following publication trend expresses in the form of graphic visualization, which is analyzed using VOSviewer software. Overall, articles with the keyword virtual laboratory published in the late 2020-2021 period focus on its relationship with Covid 19 and evaluation. This focus of research shows that during the past year, the focus of research is how to evaluate learning through virtual laboratories.

Visualization formats of Patient-Reported Outcomes in clinical practice: a systematic review about preferences and interpretation accuracy. (Preprint)

BACKGROUND The use of Patient-Reported Outcomes (PROs) for individual patient management within clinical practice is becoming increasingly important. However, there is no consensus on which graphic visualization format of PRO scores is most suitable. OBJECTIVE This systematic review evaluated evidence for graphic visualization of PROs in clinical practice for patients and clinicians, including preferences, interpretation accuracy, and guidance for clinical interpretation of PRO scores. METHODS We extracted studies published between 2000 and 2020 from CINAHL, PubMed, PsychInfo and Medline. Studies included patients ≥18 years old from daily clinical practice. Papers not available in English, without full-text access or that did not specifically describe PRO visualization were excluded. Outcome measures were: visualization preferences; interpretation accuracy; guidance for clinical interpretation. RESULTS We included 26 out of 789 papers for final analysis. Most frequently studied formats were: bar charts, line graphs and pie charts. Patients preferred bar charts and line graphs as these were easy and quick for retrieving information about their PRO scores over time. Clinicians’ interpretation accuracy was similar among graph formats. Scores were most often compared with patients’ own previous scores; to guide clinical interpretation, scores were compared to norm population scores. Different add-ons improved graph interpretability for patients and clinicians, e.g. using colors, descriptions of measurement scale directionality, descriptive labels and brief definitions. CONCLUSIONS Although we found no predominant format for graphic visualization of PRO scores, straightforward formats like bar charts and line graphs were preferred by both patients and clinicians. Additionally, detailed clarification of graph content is essential.

Development of spatial thinking in first year students of engineering specialties

The article considers issues of development of spatial thinking in students in the process of studying graphic disciplines. The relevance of the study is dictated by the specifics of competencies in the application of the laws of geometric formation of the future builder. The subject of the study is the formation of spatial thinking among engineering students through the study of the course of engineering and computer graphics. The peculiarity of the student's spatial thinking is manifested through the perception of reality, the ability to see the design result, the combination of actions and operations, as well as graphic visualization skills. The obtained results revealed the dependence of the conditions of reproduction of the form by students (reproductive knowledge) on their mastery of theoretical knowledge and acquired skills in performing images.

Toward a function library for statistical plotting with XSLT and SVG

Computational textual humanities research often makes use of descriptive statistics and graphic visualization to communicate quantitative information about textual objects of study. SVG is capable of rendering any chart or graph a user might wish to deploy, but there is no standardized function library for XSLT or XQuery comparable to, for example, the support for statistical analysis and visualization available in Python Pandas, Julia, and R. Neither is there any standard XSLT or XPath visualization library comparable to the D3.js (“Data-Driven Design”) JavaScript library that has come to dominate high-quality informational graphics on the World Wide Web. This paper begins to explore the possibility of developing such library resources without leaving the XML ecosystem.

The economic strength and tax capacity of the Krasnoyarsk Krai: Challenges and the prospects for development

Subject. The article discusses the prospects for the development of the Krasnoyarsk Krai and the implementation of the import substitution programme. Objectives. The article aims to analyze the tax potential of the Krasnoyarsk Krai, highlight the main problems, and identify possible directions for further development of the Krai. Methods. For the study, we used systems and institutional approaches, the methods of statistical and comparative analyses, and data tabular and graphic visualization. Results. The article identifies the main obstacles to the sustainable development of the Krasnoyarsk Krai. Conclusions. The Krasnoyarsk Krai has a strong economic and resource potential for further development, which is not being implemented properly.