Sportsman’s Mental State Evaluation and Early Warning Method Using Decision Tree

Aiming at the intelligent needs of psychological state assessment of university students, the text information-based psychological problem identification approach is investigated in the paper. This approach uses the text of student forums within universities as the database and introduces the convolutional neural network (CNN) model in deep learning, which contains a convolutional layer, a pooling layer, and a fully connected layer. After the convolution is completed, the convolution result is de-linearized by the activation function, and then pooling is performed to improve the fitting ability of the network for nonlinearities. For data processing, behavioral features attribute features, content features, and social relationship features are extracted from text information as the input of the CNN by using the decision tree. The psychological lexicon of expertise (LIWC) is used to enhance the efficiency of text word frequency statistics when performing text content extraction. To evaluate the performance of the proposed method, simulations are performed in the open dataset of CLPsyh2017 ReachOut Forum, and the FastText method is used as a comparison. The results show that the CNN model achieves an accuracy of 0.71 in the full-sample domain, which is significantly higher than that of the FastText model at 0.64. In the early warning evaluation of mental states, the CNN performance is better than that of FastText.

Unraveling Contradictions: Which Glosses Facilitate Reading Comprehension Among ELLs, and Why?

This critical literature review provides study details for 36 studies examining the effect of glossing for language acquisition among English language learners (ELLs). Useful tables include specificity of participants, gloss types, target vocabulary items and text information about all studies. An analysis of these studies reveals that glossing is an effective means to enhance reading comprehension among ELLs. However, gloss language—whether L1 or English, may depend on learner factors. Other findings include the importance of proximity of gloss to text and the need for glosses that do not require readers to leave the text to access meaning. Considerations such as text genre, text length, targeted items for glossing, number of items to gloss, and gloss presentation are also examined and discussed, including which gloss types may result in trade-offs when glossing is used as a means to promote incidental vocabulary acquisition through independent reading. Several recommendations for further research are offered.

LoG and Structural Based Arbitrary Oriented Multilingual Text Detection in Images/Video

Text in an image or a video affords more precise meaning and text is a prominent source with a clear explanation of the content than any other high-level or low-level features. The text detection process is a still challenging research work in the field of computer vision. However, complex background and orientation of the text leads to extremely stimulating text detection tasks. Multilingual text consists of different geometrical shapes than a single language. In this article, a simple and yet effective approach is presented to detect the text from an arbitrary oriented multilingual image and video. The proposed method employs the Laplacian of Gaussian to identify the potential text information. The double line structure analysis is applied to extract the true text candidates. The proposed method is evaluated on five datasets: Hua's, arbitrarily oriented, multi-script robust reading competition (MRRC), MSRA and video datasets with performance measures precision, recall and f-measure. The proposed method is also tested on real-time video, and the result is promising and encouraging.

Digital Mining Algorithm of English Translation Course Information Based on Digital Twin Technology

Cross-language communication puts forward higher requirements for information mining in English translation course. Aiming at the problem that the frequent patterns in the current digital mining algorithms produce a large number of patterns and rules, with a long execution time, this paper proposes a digital mining algorithm for English translation course information based on digital twin technology. According to the results of word segmentation and tagging, the feature words of English translation text are extracted, and the cross-language mapping of text is established by using digital twin technology. The estimated probability of text translation is maximized by corresponding relationship. The text information is transformed into text vector, the semantic similarity of text is calculated, and the degree of translation matching is judged. Based on this data dimension, the frequent sequence is constructed by transforming suffix sequence into prefix sequence, and the digital mining algorithm is designed. The results of example analysis show that the execution time of digital mining algorithm based on digital twin technology is significantly shorter than that based on Apriori and Map Reduce, and the mining accuracy rate reached more than 80%, which has good performance in processing massive data.

Como ler um texto acadêmico? Diretrizes para estudantes universitários

Objetivo. Propor diretrizes para orientar estudantes universitários na leitura de textos acadêmicos. Desenvolvimento. O artigo apresenta dados sobre a importância do desenvolvimento de um repertório de leitura eficiente e ações a serem apresentadas pelos estudantes para que sejam capazes de ler textos acadêmicos de forma mais produtiva e crítica, divididas em oito diretrizes, sendo elas: caracterizar a estrutura de um texto acadêmico; definir objetivos para a leitura; elaborar perguntas com base no título e subtítulos; avaliar a própria compreensão do texto; avaliar as informações apresentadas; identificar informações desconhecidas; relacionar as informações do texto com outras fontes de informação; e produzir algo novo a partir da leitura. Implicações. Espera-se que as diretrizes apresentadas auxiliem estudantes ou profissionais que necessitem aperfeiçoar o repertório de leitura de textos acadêmicos, e que possam utilizar esse conhecimento também diante de outras fontes de informação, examinando notícias e textos de forma mais crítica e autônoma.Palavras-chave. Leitura funcional; Artigo científico; Avaliação crítica; Ensino superior; Letramento científico. How to read an academic text? Guidelines for college studentsAbstract:Objective. Propose guidelines to guide university students in the reading of academic texts. Development. The article presents data on the importance of developing an efficient reading repertoire and actions to be presented by students so that they are able to read academic texts in a more productive and critical way, divided into eight guidelines, which are: to characterize the structure of an academic text; define objectives for reading; prepare questions based on title and subtitles; evaluate the very understanding of the text; evaluate the information presented; identify unknown information; relate text information to other sources of information; and produce something new from reading. Implications. It is expected that the guidelines presented can help students or professionals who need to improve the repertoire of reading academic texts, and who can use this knowledge also to read other sources of information, examining news and texts in a more critical and autonomous way.Keywords. Functional reading; scientific article; critical evaluation; higher education; scientific literacy.

DEVELOPMENT OF A MATHEMATICAL MODEL FOR A NEURAL NETWORK FOR RECOGNIZING TEXT INFORMATION

The article considers a mathematical model of a system that provides recognition of images that represent text or use similar information in the generation process.