A Visual Pattern of Two Decades of Literature on Mobile Learning: A Bibliometric Analysis

Mobile learning, or m-Learning, has grown in popularity significantly over the last few decades, as evidence of educators and students worldwide using the device as a teaching and learning tool continues to accumulate. The pattern of mobile-learning research from 2001 to 2020 is determined by bibliometric analysis. The study retrieved 3,874 documents for further analysis, based on the keywords associated with mobile learning in the article’s title. The maps depicted the connections between the researchers, countries, all keywords, titles, and abstracts. The title and abstract of this study are used to visualise the co-occurring terms of various phases or concepts associated with mobile learning that were extracted from the Scopus database. The findings indicate strong and direct connections between the concepts in e-learning, implying a significant and direct research connection. China was the leading country in mobile-learning research, and the leading journal was Computers and Education. The top author’s keywords in terms of co-occurrence were "mobile learning", "e-learning", "students", "learning systems", and "m-learning". To conduct a two-decade analysis, this study excludes any publications from the years 1984 and 2021. These critical analyses of prior work are valuable and indispensable resources for mobile-learning scholars and practitioners. It is believed that online-learning applications have increased students’ engagement; and it has eliminated the accessibility gap. Consequently, mobile learning is expected to maintain its popularity over the next few decades.

Multifractal Functional Connectivity Analysis of Electroencephalogram Reveals Reorganization of Brain Networks in a Visual Pattern Recognition Paradigm

The human brain consists of anatomically distant neuronal assemblies that are interconnected via a myriad of synapses. This anatomical network provides the neurophysiological wiring framework for functional connectivity (FC), which is essential for higher-order brain functions. While several studies have explored the scale-specific FC, the scale-free (i.e., multifractal) aspect of brain connectivity remains largely neglected. Here we examined the brain reorganization during a visual pattern recognition paradigm, using bivariate focus-based multifractal (BFMF) analysis. For this study, 58 young, healthy volunteers were recruited. Before the task, 3-3 min of resting EEG was recorded in eyes-closed (EC) and eyes-open (EO) states, respectively. The subsequent part of the measurement protocol consisted of 30 visual pattern recognition trials of 3 difficulty levels graded as Easy, Medium, and Hard. Multifractal FC was estimated with BFMF analysis of preprocessed EEG signals yielding two generalized Hurst exponent-based multifractal connectivity endpoint parameters, H(2) and ΔH15; with the former indicating the long-term cross-correlation between two brain regions, while the latter captures the degree of multifractality of their functional coupling. Accordingly, H(2) and ΔH15 networks were constructed for every participant and state, and they were characterized by their weighted local and global node degrees. Then, we investigated the between- and within-state variability of multifractal FC, as well as the relationship between global node degree and task performance captured in average success rate and reaction time. Multifractal FC increased when visual pattern recognition was administered with no differences regarding difficulty level. The observed regional heterogeneity was greater for ΔH15 networks compared to H(2) networks. These results show that reorganization of scale-free coupled dynamics takes place during visual pattern recognition independent of difficulty level. Additionally, the observed regional variability illustrates that multifractal FC is region-specific both during rest and task. Our findings indicate that investigating multifractal FC under various conditions – such as mental workload in healthy and potentially in diseased populations – is a promising direction for future research.

Health Risk Detection and Classification Model Using Multi-Model-Based Image Channel Expansion and Visual Pattern Standardization

Although mammography is an effective screening method for early detection of breast cancer, it is also difficult for experts to use since it requires a high level of sensitivity and expertise. A computer-aided detection system was introduced to improve the detection accuracy of breast cancer in mammography, which is difficult to read. In addition, research to find lesions in mammography images using artificial intelligence has been actively conducted in recent days. However, the images generally used for breast cancer diagnosis are high-resolution and thus require high-spec equipment and a significant amount of time and money to learn and recognize the images and process calculations. This can lower the accuracy of the diagnosis since it depends on the performance of the equipment. To solve this problem, this paper will propose a health risk detection and classification model using multi-model-based image channel expansion and visual pattern shaping. The proposed method expands the channels of breast ultrasound images and detects tumors quickly and accurately through the YOLO model. In order to reduce the amount of computation to enable rapid diagnosis of the detected tumors, the model reduces the dimensions of the data by normalizing the visual information and use them as an input for the RNN model to diagnose breast cancer. When the channels were expanded through the proposed brightness smoothing and visual pattern shaping, the accuracy was the highest at 94.9%. Based on the images generated, the study evaluated the breast cancer diagnosis performance. The results showed that the accuracy of the proposed model was 97.3%, CRNN 95.2%, VGG 93.6%, AlexNet 62.9%, and GoogleNet 75.3%, confirming that the proposed model had the best performance.

Presencia y valor de los círculos rojos en murales teotihuacanos / Presence and value of red circles in teotihuacan murals

En la pintura mural prehispánica se plasmaron símbolos, escenas reales y ficticias, que nos permiten penetrar el universo ideológico de sus creadores. En Teotihuacán, durante los siglos XIX y XX se recuperó una gran cantidad de vestigios de pintura mural cuyo registro forma parte de la memoria arqueológica de la ciudad. Este trabajo hace un breve recuento de los hallazgos de pintura mural en la urbe del Clásico, hasta los albores del siglo XXI. Gracias al registro detallado, visualizamos la presencia constante de una forma geométrica que podría portar un simbolismo particular: el círculo rojo. Se presenta entonces un recorrido por la arquitectura que ostentó este diseño, para lograr un primer acercamiento al patrón visual que los artistas teotihuacanos alcanzaron con esta forma y al posible valor iconográfico de los círculos rojos en el discurso mural de la ciudad. Abstract: In Teotihuacan during the XIX and XX century many remains of wall paintings were recovered from the inside of houses and public buildings. The goal of this research paper is to give a brief account of the mural paintings discovered at the ancient city till the beginning of the XXI century, we have implemented a systematic registration project, which in the end will constititute one of the most complete memories of this artistic expression. Thanks to the detailed surveys, we have been able to recognize the constant presence of geometric shapes that could carry a particular symbolism: the Red Circle. There is then a tour of the architecture that held this design, whit the aim of achieving a first approach to visual pattern that Teotihuacan artists succeeded whit this form, and the possible iconographic value the red circles in the discourse mural in the city. Keywords: Teotihuacan; architecture of Teotihuacan; mural painting; red circles; solar theme. Résumé : À Teotihuacán, au cours des XIXe et XXe siècles, de nombreux vestiges de peintures murales ont été retrouvés, dont l'archivage fait partie de la mémoire archéologique de la ville. Cet ouvrage retrace brièvement l’évolution des découvertes de la peinture murale dans la période classique de la ville jusqu’a l’aube du XXIe siècle. Grâce à ce registre détaillé, nous visualisons la présence constante d’une forme géométrique pouvant porter un symbolisme particulier: le cercle rouge. Une visite guidée de l’architecture qui a mis en lumière ce dessin est présentée, a fin de réaliser une première approche du motif visuel que les artistes de Teotihuacan ont élaboré avec cette forme et de la valeur iconographique des cercles rouges dans le discours mural de la ville. Mots-clés : Teotihuacan ; architecture Teotihuacan ; peinture murale ; cercles rouges ; thème solaire.

The influence of expertise and experimental paradigms on the visual behavior of tennis athletes in returning a serve

To return a serve, one must pick up information from the server’s kinematics and anticipate the ball trajectory. Although the perceptual requirements are important, the literature diverges in terms of the differences between experts and novices as well as the importance of the experimental paradigm (in-situ vs. video-based) for the results. This study aimed to address both concerns. We compared experts’ (n=7, 20.6±1.1 year of age) and novices’ (n=7, 20.0±0.4 years of age) visual pattern when returning a serve (Experiment 1) and the influence of the experimental paradigm in experts (Experiment 2). Experts fixated more and longer the upper body and ball, while novices showed a more distributed pattern and with longer fixations outside of the server’s body. Also, the pattern was different when comparing in-situ and laboratory settings, differing mainly in fixation frequency. The influence of expertise was observed in qualitative (relative) and quantitative (absolute) measures of visual behavior with the setting having an important influence. Thus, studies should be as close to the actual situation if trying to understand experts’ behavior.