This study aims to analyze the size effect of the STEM-based mind mapping learning model to increase students' scientific literacy in the revolutionary era 4.0. This type of research is meta-analysis. The research samples came from 15 national and international journals published from 2018-2023. The method for selecting this meta-analysis research data is through the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Search for data sources through Google Scholar, Wiley, Eric and ProQuest. Data source collection techniques are direct observation and documentation through online databases. Data analysis is a quantitative analysis by calculating the effect size, standard error and average value with the help of the JSAP application. The results showed that from this study it could be concluded that the combined effect size value was (d = 1.30; p < 0.05) high criteria. These findings explain that STEM-based mind mapping models are more effective in improving scientific literacy skills in the 4.0 revolution era than conventional learning models. The STEM-based mind mapping learning model provides a new breakthrough in the world of educational technology.
In this study, hydraulic pressure generation and small-scale cylindrical hydromechanical deep-drawing experiments were conducted using a novel die-integrated active high-pressure generation system. The most significant feature is the installation of a hydraulic pressure-generating piston structure inside the die, which enables a high-pressure generation process of 100 MPa or higher inside the die. In addition, by taking advantage of the size effect of a smaller die, a high hydraulic pressure is actively generated using the same equipment as in conventional drawing processes. It was discovered that a piston installed in the die can actively generate a hydraulic pressure of 100 MPa or higher based on the Pascal principle. By downsizing the die, a hydraulic pressure of 100 MPa or higher can be generated using only the power of a small press machine (50 kN). By actively applying high hydraulic pressure counter and radial pressures, small-scale drawability can be significantly improved. Furthermore, the application of the proposed system to single-action presses and progressive dies can enable hydromechanical deep drawing with optimized conditions for each process in a single motion.
The research objective is to determine the effectiveness of the Internet of Things (IoT)-based Flipped Classroom model on students' critical thinking skills. This type of research is meta-analysis research. Data sources come from national and international journals. The inclusion criteria in this research are that research must come from journals and proceedings indexed by SINTA, WOS and Scopus; Research from journals published from 2019-2023; Research must use experimental or quasi-experimental methods; Data source searches must be from the G,oogle Scholar, Taylor & Francis, ScienceDirect, IEEE, and ERIC databases; and Research reports values (t), (r) and (f) and sample size > 20 students. Data analysis with the help of the JSAP application. The results of this study conclude that the summary effect size or mean effect size (rRE = 0.764; p < 0.001) has a high influence. In this meta-analysis, the author, year of publication, country of research, values (r), (t), and (f) are analyzed. These findings show that the Internet of Things (IoT) based flipped classroom model is effective in improving students' critical thinking skills
The rapid damage estimation of building group in Gunkanjima is carried out through the synchronized measurement of vibration sensor network using MEMS acceleration sensors. The anomalous behavior is firstly detected by tracking the observed acceleration time series of each building. Then, the global damage of each building is investigated by singular value decomposition of the whole frame. Finally, the local damage within each building is scrutinized by evaluating the spectral ratio between observation points of the partial frame. This paper deals with the global and local damage assessment to elucidate the causes of anomalous behaviors reported in the previous paper.
