Automatic mesh analysis technique by knowledge-based system

technical reportThe finite element analysis technique has been recognized as a very important tool to solve various engineering problems, such as structural analysis, heat transfer, and fluid dynamics. The key point to the technique is discretization of the domain of interest into many finite elements. A good result is strongly dependent on the number and arrangement of meshes. However, it is very difficult to generate efficient finite element meshes, although there are many finite element analysis techniques available. The adaptive mesh generation algorithm has been implemented in the expert system in order to save both time and money in the finite element analysis process. It i s n o t required for a user to know detail information about the finite element analysis processes or computer science to test structural analysis. To verify efficiency of EFEM, analyses for planar and shell domain models have been performed in two and three dimensions respectively

Smoking, ADHD, and Problematic Video Game Use: A Structural Modeling Approach

Problematic video game use (PVGU), or addiction-like use of video games, is associated with negative physical and mental health problems as well as problems in social and occupational functioning. Possible contributors to PVGU include frequency of play, cigarette smoking, and ADHD. The aim of the current study was to explore the relationships among PVGU, cigarette smoking, ADHD, and frequency of play simultaneously using a structural modeling approach. Secondary data analysis was conducted on 2,801 video game users (Mage = 22.43 years, SDage = 4.7; 93% male) who completed an online survey comprising measures of PVGU, ADHD symptomatology, smoking behavior, and hours of video game use. The full model fit the data well: χ2 (2) = 2.017, p \u3e .05; RMSEA = 0.002 (90% CI [.000, .038]); CFI = 1.000; SRMR = .004. Absolute values of all standardized residuals were less than 0.1. All freely estimated paths were statistically significant. ADHD symptomatology, smoking behavior, and hours of video game use explained 41.8% of variance in PVGU. ADHD symptomatology, cigarette use, and video game use may all contribute to PVGU, which is consistent with past studies that examined these variables independently. Tracking these variables may be useful for PVGU prevention and assessment. The measurement model fit well, suggesting that Young’s Internet Addiction Scale, adapted for video game use, and Problem Videogame Playing Scale measure the same construct. Findings using either measures may be compared to each other, and both measures may be used as a screener of PVGU. The field of video game research may benefit from studying additional variables that help explain PVGU, specific treatment protocols for PVGU, and the effect of ADHD or smoking treatment on PVGU

Implementation and characteristics of rule-based system for the finite element analysis

Journal ArticleIt it well known that the analysis of process for the finite element method is tedious and errorprone steps. Considering the importance of the task of engineering analyses, such as structural analysis, heat transfer, fluid flow simulation, and electromagnetic potential, many researchers have tried to develop better and easier systems. Meanwhile, expert systems have been developed in various areas, such as DENDRAL, MYCIN, and XCON. There are two main reasons for developing expert systems. First, an expert system can facilitate the dissemination of vital knowledge to a certain organization with a reasonable cost. Second, an expert system does not suffer from humahpFoblems such as confusion to that it can apply appropriate rules to the problem. It is obvious that development of an expert system for finite element mesh generation can save both time and money in the finite element analysis process. A rule-based system for optimal finite element mesh generation, EFEM has been developed and implemented in powerful interactive solid modeler. Because required knowledge is translated into rules, it is not required to know detail information about the finite element analysis processes or computer science to test structural analysis. The implementation of the EFEM has been analyzed

STORYBOOK TO ENGAGE IN LITERACY PRACTICES IN ELEMENTARY SCHOOL IN KOREA

This study investigates ways to promote English literacy through storytelling methods based on sociocultural perspectives of literacy in Korean public elementary school settings. As a teacher researcher, I ran a storytelling afterschool program to develop English literacy using English storybooks. 14 of 3rd and 4th graders including 6 focal students participated in the study. The research findings show that storybook was useful to engage students in literacy practices in Korean elementary school context where English is taught as a foreign language. While implementing English storybooks, strengthening affective aspects within ZPD was significant. Also, scaffolding should be done in various ways. Even though the class was pursuing literacy development, oral language development was also followed. Storybook made it possible to implement literacy knowledge with ease. In teaching English storybooks in Korean context, teacher needs to consider characteristics of foreign language learners, take advantage of teaching strategies used by regular classes, and make students reflective on themselves

Estimating δ15N and δ13C in Barley and Pea Mixtures Using Near-Infrared Spectroscopy with Genetic Algorithm Based Partial Least Squares Regression

Stable isotope measurements have been increasingly used as a method to obtain information on relationships between plants and their environment (Dawson et al., 2002). Stable isotopes are seen as a powerful tool for advancing our knowledge on stock cycling and, nitrogen and carbon isotopic compositions have provided key insights into biogeochemical interactions between plants, soils and the atmosphere (Robinson, 2001). For the stable isotope measurements, the δ13C isotopic signature has been used successfully to disentangle physiological, ecological and biogeochemical processes and, δ15N studies have significantly improved our knowledge on nitrogen cycling pathways and nitrogen acquisition by plants (Vallano and Sparks, 2008). For the stable isotope measurements, traditional laboratory methods using isotope analysis are accurate and reliable, but usually time-consuming and expensive. Near-infrared spectroscopy (NIRS) analysis provides rapid, accurate and less expensive estimation. NIRS have been made to estimate herbage parameters using statistical methods such as multiple linear regression and partial least square regression (PLSR). PLSR uses all available wavebands in multivariate calibration for quantitative analysis of the spectral data. However, previous studies indicated that PLSR with waveband selection might improve their predictive accuracy in multivariate calibration at laboratory (Leardi, 2000) and the selection of appropriate wavelengths can refine the predictive accuracy of the PLS model by optimizing important spectral wavebands both in laboratory NIRS (Jiang et al., 2002). To optimize important spectral wavebands by wavelength selection, genetic algorithms (GA) is widely used, because GA has the ability to simulate the natural evolution of an individual and GA is well suited for solving variable subset selection problems (Ding et al., 1998). Barley and pea mixture is one of the most important forage species for livestock farming in Korea. To investigate nitrogen fixation and transfer in barley and pea mixture, stable isotope measurements was widely used. However, there was no research to estimate stable isotope in barley and pea mixture using NIRS in Korea. The aim of this study was to investigate performance of NIRS with PLSR using genetic algorithms based wavelength selection (GA-PLSR) and compare with PLSR without wavelength selection (FS-PLSR) for the estimation of δ15N and δ13C in barley and pea mixture