Magnetic Resonance Image from Children’s Brain by Evaluating IQ Estimator Using Kernel Support Vector Regression

Human brain explains the function of the various parts of our body. The Brain has been categorized into three parts Cerebrum, cerebellum and brain stem. In this, cerebrum plays a vital role in the brain which controls reading, thinking, learning, speech, emotions, vision, hearing and other senses. The Prefrontal cortex (PFC) is the cerebral cortex which covers the front part of the frontal lobe and the most strongly recommended in human qualities like consciousness, general intelligence, and personality. To find out one’s intelligence, most of the IQ score is commonly obtained from many diverse tests with disadvantages of no single large dataset containing psychology test scores for the IQ estimation is unavailable. In this paper deals about estimating the IQ from young children Brain MRI images with Kernel Support Vector Regression (SVR) is designed. The experimentation is carried out to verify the performance of different feature reduction by applying four extracted features Grey Matter Volume, White Matter Volume, Gyri and Sulci Surface Area with the target only as Wechsler Abbreviated Scale Intelligence (WASI) IQ Score has been collected from ABIDE II MRI images of 232 children between 6 and 15 years of age. Kernel SVR is used to estimate IQ scores between the concrete and valued IQs on using reduced features obtained from PCA, Kernel PCA, t-SNE and Kernel t-SNE with root mean square error of 1.0021, 0.459, 0.976 and 1.517 and acquired Pearson’s correlation coefficients of 0.938, 0.9864, 0.941 and 0.843 respectively.

Automatic IQ Estimation Using Stylometric Methods

Stylometry is a study of text linguistic properties that brings together various fields of research such as statistics, linguistics, computer science and more. Stylometry methods have been used for historic investigation, as forensic evidence and an educational tool. This chapter presents a method to automatically estimate individual's IQ based on quality of writing and discusses challenges associated with it. The method utilizes various text features and NLP techniques to calculate indexes which are used to estimate individual's IQ. The results show a high degree of correlation between expected and estimated IQs in cases when IQ is within the average range. Obtaining good estimation for IQs on the high and low ends of the spectrum proves to be more challenging and this work offers several reasons for that. Over the years stylometry benefitted from wide exposure and interest among researches, however it appears that there aren't studies that focus on using stylometry methods to estimate individual's intelligence. Perhaps this work presents the first in-depth attempt to do so.

THE COGNITIVE COMPETENCES OF IMMIGRANT AND NATIVE STUDENTS ACROSS THE WORLD: AN ANALYSIS OF GAPS, POSSIBLE CAUSES AND IMPACT

SummaryImmigration, immigration policies and education of immigrants alter competence levels. This study analysed their effects using PISA, TIMSS and PIRLS data (1995 to 2012,N=93 nations) for natives' and immigrants' competences, competence gaps and their population proportions. The mean gap is equivalent to 4.71 IQ points. There are large differences across countries in these gaps ranging from around +12 to −10 IQ points. Migrants' proportions grow roughly 4% per decade. The largest immigrant-based ‘brain gains’ are observed for Arabian oil-based economies, and the largest ‘brain losses’ for Central Europe. Regarding causes of native–immigrant gaps, language problems do not seem to explain them. However, English-speaking countries show an advantage. Acculturation within one generation and intermarriage usually reduce native–immigrant gaps (≅1 IQ point). National educational quality reduces gaps, especially school enrolment at a young age, the use of tests and school autonomy. A one standard deviation increase in school quality represents a closing of around 1 IQ point in the native–immigrant gap. A new Greenwich IQ estimation based on UK natives' cognitive ability mean is recommended. An analysis of the first adult OECD study PIAAC revealed that larger proportions of immigrants among adults reduce average competence levels and positive Flynn effects. The effects on economic development and suggestions for immigration and educational policy are discussed.

A ROBUST NEIGHBORHOOD TRUNCATION APPROACH TO ESTIMATION OF INTEGRATED QUARTICITY

We provide a first in-depth look at robust estimation of integrated quarticity (IQ) based on high-frequency data. IQ is the key ingredient enabling inference about volatility and the presence of jumps in financial time series and is thus of considerable interest in applications. We document the significant empirical challenges for IQ estimation posed by commonly encountered data imperfections and set forth three complementary approaches for improving IQ-based inference. First, we show that many common deviations from the jump-diffusive null can be dealt with by a novel filtering scheme that generalizes truncation of individual returns to truncation of arbitrary functionals on return blocks. Second, we propose a new family of efficient robust neighborhood truncation (RNT) estimators for integrated power variation based on order statistics of a set of unbiased local power variation estimators on a block of returns. Third, we find that ratio-based inference, originally proposed in this context by Barndorff-Nielsen and Shephard (2002, Journal of Applied Econometrics 17, 457–477), has desirable robustness properties in the face of regularly occurring data imperfections and thus is well suited for empirical applications. We confirm that the proposed filtering scheme and the RNT estimators perform well in our extensive simulation designs and in an application to the individual Dow Jones 30 stocks.