• Interdisciplinary Bio Central
• /
• v.6 no.4
• /
• pp.2.1-2.7
• /
• 2014

Sexual dimorphism in intelligence suggests that this phenotype is a sexually selected trait. This view is supported by an overrepresentation (compared to the autosomal genome) of genes affecting cognition on the X chromosome. The aim of this study is to test the hypothesis that sexual selection can explain sex and country-level differences in performance on tests of fluid intelligence. Nationally representative samples from N = 44 countries were obtained from the Programme for International Student Assessment (PISA) Creative Problem Solving (CPS), which evaluates the core of intelligence, that is novel problem solving ability. Sexual selection has the double effect of increasing the prevalence of a favored phenotype and reducing genetic variation in sexually selected traits. Matching these predictions from evolutionary theory, the average country fluid intelligence is positively correlated to sexual dimorphism after partialling out per capita GDP and the latter in turn is inversely correlated to variance in intelligence scores within populations. Males have a higher variance than females but there is a negative correlation between male-female difference in variance and sexual dimorphism in intelligence, suggesting that selection reduces variance more in the selected sex. Average country male height is negatively correlated to sexual dimorphism in intelligence, a fact that supports the notion of a trade-off between physical and intellectual competition in the context of access to females. The results of this study, if replicated, imply that genome-wide association studies of cognition may benefit from a focus on sex chromosomes, which so far have been neglected. Another implication of this study is that intelligence has continued to evolve after different human populations migrated out of Africa and possibly up to the 19th century, as suggested by the substantial variability in sex differences even between neighbouring countries.

• Journal of the Semiconductor & Display Technology
• /
• v.22 no.1
• /
• pp.134-138
• /
• 2023

This study focuses on the analysis of the results of computational fluid dynamics simulations of mist-chemical vapor deposition for the growth of an epitaxial wafer in power semiconductor technology using artificial intelligence techniques. The conventional approach of predicting the uniformity of the deposited layer using computational fluid dynamics and design of experimental takes considerable time. To overcome this, artificial intelligence method, which is widely used for optimization, automation, and prediction in various fields, was utilized to analyze the computational fluid dynamics simulation results. The computational fluid dynamics simulation results were analyzed using a supervised deep neural network model for regression analysis. The predicted results were evaluated quantitatively using Euclidean distance calculations. And the Bayesian optimization was used to derive the optimal condition, which results obtained through deep neural network training showed a discrepancy of approximately 4% when compared to the results obtained through computational fluid dynamics analysis. resulted in an increase of 146.2% compared to the previous computational fluid dynamics simulation results. These results are expected to have practical applications in various fields.

• Proceedings of the Korean Society for the Gifted Conference
• /
• 2003.05a
• /
• pp.137-138
• /
• 2003

Understanding how and why people differ is a fundamental, if distant, goal of research efforts to bridge psychological and biological levels of analysis. General fluid intelligence (gF) is a major dimension of individual differences and refers to reasoning and novel problemsolving ability. A conceptual integration of evidence from cognitive (behavioral) and anatomical studies suggeststhat gF should covary with both task performance and neural activity in specific brain systems when specific cognitive demands are present, with the neural activity mediating the relation between gF and performance. Direct investigation of this possibility will be a critical step toward a mechanistic model of human intelligence. In turn, a mechanistic model might suggest ways to enhance gF through targeted behavioral or neurobiological intervent ions, We formed two different groups as subjects based on their scholarly attainments. Each group consists of 20 volunteers(aged 16-17 years, right-handed males) from the National Gifted School and a local high school respectively. To test whether individual differences in general intelligence are mediated at a neural level, we first assessed intellectual characteristics in 40 subjects using standard intelligence tests (Raven's Advanced Progressive Matrices, Wechsler Adult Intelligence Scale, Torrance Tests of Creative Thinking) administered outside of the MR scanner. We then used functional magnetic resonance imaging (fMRl) to measure task-related brain activity as participants performed three different kinds of computerized reasoning tasks that were intended to activate the relevant neural systems. To examine the difference of neural activity according to discrepancy in general intelligence, we compared the brain activity of both extreme groups (each, n=10) of the participants based on the standard intelligence test scores. In contrast to the common expectation, there was no significant difference of brain region involved in high-g tasks between both groups. Random effect analysis exhibited that lateral prefrontal, anterior cingulate and parietal cortex are associated with gF. Despite very different task contents in the three high-g-low-g contrasts, recruitment of multiple regions is markedly similar in each case, However, on the task with high 9F correlations, the Prodigy group, (intelligence rank: >99%) showed higher task-related neural activity in several brain regions. These results suggest that the relationship between gF and brain activity should be stronger under high-g conditions than low-g conditions.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.23 no.6
• /
• pp.547-554
• /
• 2014

CVD SiC is a perfect material used for molds/dies in hot press molding of glass lens. In its fabrication process, nano-precision polishing is essential finally. For this purpose, a novel polishing method using MCF (Magnetic Compound Fluid) slurry is proposed. In this method, MCF slurry is supplied into a given gap between the workpiece and a MCF slurry carrier, and constrained within the polishing zone by magnetic forces from permanent magnet. In this paper, after an experimental rig used to actually realize the proposed method has been constructed, the fundamental polishing characteristics of CVD SiC such as the effects of process parameters including MCF slurry composition on work-surface roughness were experimentally investigated. As a result, nano-precision surface finish of CVD SiC was successfully attained with MCF slurry and the optimum process parameters for obtaining the smoothest work-surface were determined.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.4 no.1
• /
• pp.49-55
• /
• 2005

This paper presents experiments on the evaluation of characteristics of ER fluids used for vibration control of application in intelligence type process control systems. Dynamic characteristics of the actuator(beam) embedded with the ER fluid can be controlled by changing the strength of the electric field applied on the ER fluids, thus provides a mean to avoid the resonance. In case electric field is supplied to the smart structure with ER fluids, vibration energy is dissipated more than the beam without electric field, because particles in ER fluid form a chain structure in the presence of electric field. The damping and stiffness of the beam with ER fluid are increased when the applied electric field increases. The characteristics of damping and stiffness of the ER fluid with various electric field strength were investigated by conducting a vibration test of the beam with ER fluid. If it applies characteristics of the ER fluids, it will be able to apply in the PLC control system for the vibration which occurs from process system.

• Computational Structural Engineering
• /
• v.32 no.4
• /
• pp.4-10
• /
• 2019

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.11a
• /
• pp.217-218
• /
• 2021

The development of artificial intelligence in the field of construction and construction is revitalizing. The performance and development techniques of artificial intelligence are changing rapidly, but if you look at the cases of domestic construction sites, they are using technologies from 5 to 7 years ago. It is right to follow a stable method in consideration of commercialization, but the previous AI development method requires more manpower and time to develop than the current technology. In addition, in order to actively utilize artificial intelligence technology, customized artificial intelligence is required to be applied to ever-changing changes in construction sites. it is the reality As a result, even if good AI technology is secured at the construction site, it is reluctant to introduce it because there is no advantage in terms of time and cost compared to the existing method to apply it only to some processes. Currently, an AI technique with a faster development process and accurate recognition has been developed to cope with a fluid situation, so it will be important to understand and introduce the rapidly changing AI development method.

• Journal of Drive and Control
• /
• v.18 no.4
• /
• pp.92-97
• /
• 2021

• 한국전산유체공학회:학술대회논문집
• /
• 2003.10a
• /
• pp.19-20
• /
• 2003

Brownian-dynamics simulation on highly charged colloidal suspensions is performed by employing Tokuyama effective force recently proposed. The radial distribution function suggests that there exist three novel phases, a gas phase, a liquid droplet phase, and a face-centered cubic (FCC) crystal droplet phase, depending on the minimum values of that potential. The dynamics of droplet growth is also investigated both in liquid droplet phase and in crystal droplet phase. Thus, different types of characteristic growth stages are found.

• Korean Institute of Interior Design Journal
• /
• v.20 no.3
• /
• pp.143-151
• /
• 2011

With today's new media environment throughout Ubiquitous information innovation, live and dynamic fluid space is being created by integrating organic integration between electronic space and physical space and transplanting intelligence to materials. In other words, perception occurs in fluid space itself in a new media environment so has complicatedly organic relationship with environment and humans. In addition, emotion, time and movement have actively attempted to enter the space so designs appealing to humans' emotions are made through stimulation of synaesthetic sensory organs. This can be understood in the same context that media is eventually expansion of human body. Fluid space has characteristics of a live organism with factors such as sensor, perception and behavior so it needs to interpret perceptual system relationally and synthetically through an organic study method. This study looks into characteristics of organic perceptual system in terms of the meaning that fluid space with movements have as the sensory-perceptive subject and accordingly makes the world more sufficient as the third space, prepares a possibility to get out of limited five senses, and will develop fluid space as the organic environment making stimulation by itself.