• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.837-850
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• 2002

In this paper, we propose an EEG-based response time prediction method during a yes/no cognitive decision task. In the experimental task, a subject goes through responding of visual stimulus, understanding the given problem, controlling hand motions, and hitting a key. Considering the subject's varying brain activities, we model subjects' mental states with defining CT (cut time), ST (selection time), and RP (repeated period). Based on the assumption between ST and RT in the mental model, we predict subjects' response time by detection of selection time. To recognize the subjects' selection time ST, we extract 3 types of feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, ${\gamma}$ waves in 4 electrode pairs combined by spatial relationships. From the extracted features, we construct specific rules for each subject and meta rules including common factors in all subjects. Applying the ST detection rules to 8 subjects gives 83% success rates and also shows that the subjects will hit a key in 0.73 seconds after ST detected. To validate the detection rules and parameters, we test the rules for 2 subjects among 8 and discuss about the experimental results. We expect that the proposed detection method can be a basic technology for brain-computer-interface by combining with left/right hand movement or yes/no discrimination methods.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.3
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• pp.207-221
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• 2020

This study conducted a meta-analysis on the effects of innovation, risk-taking, and enterprising on entrepreneurship. From 2013 to 2020, 392 papers, which were judged as quantitative research from doctoral and master thesis, and academic journals published in Korea were selected as research subjects. 28 duplicates of thesis and thesis are excluded. A total of 52 papers were finally selected, excluding 312 papers that were insufficient to be used as research data because there were no statistical values such as correlation coefficients. For the 52 selected papers, the homogeneity of the variables was first verified. As a result of the homogeneity test, the innovativeness, risk-taking, initiative, and entrepreneurship education all showed great effects on heterogeneity, and the average effect size was analyzed by random effect model. The average effect size analyzed was 0.38 ~ 0.49, and all four variables showed moderate average effect size. As a result of analyzing the average effect size by forest plot, all showed proper results. From the results of funnel plot analysis of entrepreneurship education, published errors were confirmed asymmetric. Research data on entrepreneurship education shows that it cannot represent the whole. It is a structural equation model with entrepreneurship and entrepreneurial intention as a parameter. Iinnovation and risk-taking have an impact on entrepreneurship by taking entrepreneurship education as a parameter. Initiative had an effect on the entrepreneurial intention a business, regardless of entrepreneurship education. In a number of studies, university entrepreneurship education has had an impact on the entrepreneurial intention. It should be changed to entrepreneurship education that combines theory and practice. Entrepreneurship education should be transformed into continuous and field-oriented education.

• The Korean Journal of Pesticide Science
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• v.9 no.3
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• pp.199-204
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• 2005

The herbicidal activities against barnyardgrass (Echinochloa crus-galli) by R-groups on the hexahydroisoindol-1-one ring of new 2-(4-chloro-5-(2-chloroallyloxy)-2-fluorophenyl) -3-thioalkoxy-2,3,4,5,6,7-hexahydroisoindol-1-one derivatives were studied using molecular holographic quantitative structure-activity relationships (HQSAR) methodology. Based on the results, the statistical results of the optimised HQSAR model (I-2) exhibited the best predictability and fitness for the herbicidal activities based on the cross-validated value ($r^2_{cv.}$ or $q^2=0.714$) and non-cross-validated value ($r^2_{ncv.}=0.922$), respectively. From the based graphical analyses of atomic contribution maps, herbicidal activities against barnyardgrass were confirmed depends upon the C4-C6 atoms of hexahydroisoindoline-l-one ring, carbon atom of ortho-position and meta-methyl group of 3-tolylthio substituent (8).

• Journal of Digital Convergence
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• v.13 no.9
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• pp.191-199
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• 2015

The Journal of Digital Policy & Management. This space is for the abstract of your study in English. In this paper, we propose a u-convergence Tourist Information 3.0 System using Flow Theory. It generates a sense of u-challenge and u-skills to maximize the enjoyment of tourists is u-convergence Tourist Information 3.0. This is a challenge to good sense and adjust the rating of the Convergence Contents information quality(CCIQ) analysis to maximize the enjoyment of tourists. Convergence Contents information quality(CCIQ) of the conductive continuity of the content closed antecedents u-conductive sense, the tourist synchronization adequacy may generate data that can be analyzed. Content Information Quality of rating is the leading factor in the ability of the u-skill mastery of tourists, can generate data availability. The result is to create a meta-model is referred to as content information to reach the best quality maximize enjoyment. Design a sense of u-challenge the skill of the information quality of the tourist information content has the advantage of being able to identify the data formation has the pleasure of tourists. By applying to future national competent standard it is expected to maximize the enjoyment of the job.

• Journal of the Korean Geotechnical Society
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• v.40 no.4
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• pp.169-178
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• 2024

While stable mid- to large-scale underground hydrogen storage infrastructures are needed to meet the rapidly increasing demand for hydrogen energy, evaluating the safety of explosion vibrations in adjacent buildings is becoming important because of gas explosions in underground hydrogen storage facilities. In this study, a numerical analysis of vibration safety effects on nearby building structures was performed assuming a hydrogen gas explosion disaster scenario in a low-depth underground hydrogen storage facility. A parametric study using a meta-model was conducted to predict changes in ground dynamic behavior for each combination of ground properties and to analyze sensitivity to geotechnical influencing factors. Directly above the hydrogen storage facility, the unit weight of the ground had the greatest influence on the change in ground vibration due to the explosion, whereas, farther away from the facility, the sensitivity of dynamic properties was found to be high. In addition, in evaluating the vibration stability of ground building structures based on the predicted ground vibration data and blasting vibration tolerance criteria, in the case of large reinforced concrete building structures, the ground vibration safety was guaranteed with a separation distance of about 10-30 m.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.1047-1055
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• 2014

Background: MicroRNAs (miRNAs) are an abundant class of endogenous small non-coding RNAs of 20-25 nucleotides in length that function as negative gene regulators. MiRNAs play roles in most biological processes, as well as diverse human diseases including cancer. Recently, many studies investigated the association between SNPs in miR-146a rs2910164, miR-196a2 rs11614913, miR-149 rs229283, miR-499 rs3746444 and colorectal cancer (CRC), which results have been inconclusive. Methodology/Principal Findings: PubMed, EMBASE, CNKI databases were searched with the last search updated on November 5, 2013. For miR-196a2 rs11614913, a significantly decreased risk of CRC development was observed under three genetic models (dominant model: OR = 0.848, 95%CI: 0.735-0.979, P = 0.025; recessive model: OR = 0.838, 95%CI: 0.721-0.974, P = 0.021; homozygous model: OR = 0.754, 95%CI: 0.627-0.907, P = 0.003). In the subgroup analyses, miR-$196a2^*T$ variant was associated with a significantly decreased susceptibility of CRC (allele model: OR = 0.839, 95%CI: 0.749-0.940, P = 0.000; dominant model: OR = 0.770, 95%CI: 0.653-0.980, P = 0.002; recessive model: OR = 0.802, 95%CI: 0.685-0.939, P = 0.006; homozygous model: OR = 0.695, 95%CI: 0.570-0.847, P = 0.000). As for miR-149 rs2292832, the two genetic models (recessive model: OR = 1.199, 95% CI 1.028-1.398, P = 0.021; heterozygous model: OR = 1.226, 95% CI 1.039-1.447, P = 0.013) demonstrated increased susceptibility to CRC. On subgroup analysis, significantly increased susceptibility of CRC was found in the genetic models (recessive model: OR = 1.180, 95% CI 1.008-1.382, P = 0.040; heterozygous model: OR = 1.202, 95% CI 1.013-1.425, P = 0.013) in the Asian group. Conclusions: These findings supported that the miR-196a2 rs11614913 and miR-149 rs2292832 polymorphisms may contribute to susceptibility to CRC.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.181-200
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• 2020

This study used the OLS model to estimate the determinants affecting the tenure of a home and then compared the predictive power of each model with SVM, Decision Tree, Random Forest, Gradient Boosting, XGBooest and LightGBM. There is a difference from the preceding study in that the Stacking model, one of the ensemble models, can be used as a base model to establish a more predictable model to identify the volume of housing transactions in the housing market. OLS analysis showed that sales profits, housing prices, the number of household members, and the type of residential housing (detached housing, apartments) affected the period of housing ownership, and compared the predictability of the machine learning model with RMSE, the results showed that the machine learning model had higher predictability. Afterwards, the predictive power was compared by applying each machine learning after rebuilding the data with the influencing variables, and the analysis showed the best predictive power of Random Forest. In addition, the most predictable Random Forest, Decision Tree, Gradient Boosting, and XGBooost models were applied as individual models, and the Stacking model was constructed using Linear, Ridge, and Lasso models as meta models. As a result of the analysis, the RMSE value in the Ridge model was the lowest at 0.5181, thus building the highest predictive model.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1008-1021
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• 2006

Product line engineering(PLE) is one of the recent and effective reuse approaches that enables developing a number of applications by instantiating a core asset. Elements of a core asset are product line architecture(PLA), component, and decision model. Among these elements, PLA is the key element since it defines the overall structure of the core asset. Although numerous PLE methodologies have been introduced, it is still unclear what should be the elements of a PLA and how to systematically instantiate it for specific applications. Formal specifications can play a key role in defining detailed and precise instantiation process. In this paper, we first present a meta model of PLA and show how to specify PLA in a formal language, Object-Z. Then, we propose instantiation rules using formal specification and those rules precisely define constraints for instantiating PLA. By applying the proposed formal specification, we believe PLA instantiation can be carried out precisely and correctly, yielding high quality software development.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.15 no.6
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• pp.10-23
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• 2016

With requiring circumspections using big data, this study attempts to develop and apply the search method for audit issues relating to the ITS policy or program. For the foregoing, the auditing process of the board of audit and inspection was converged with the theoretical frame of boundary analysis proposed by William Dunn as an analysis tool for audit issues. Moreover, we apply the text mining technique in order to computerize the analysis tool, which is similar to the boundary analysis in the concept of approaching meta-problems. For the text mining analysis, specific model we applied the antisymmetry-symmetry compound lexeme-based LDA model based on the Latent Dirichlet Allocation(LDA) methodologies proposed by David Blei. The several prime issues were founded through a case analysis as follows: lack of collection of traffic information by the urban traffic information system, which is operated by the National Police Agency, the overlapping problems between the Ministry of Land, Infrastructure and Transport and the Advanced Traffic Management System and fabrication of the mileage on digital tachograph.

• Journal of the Korea Convergence Society
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• v.8 no.2
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• pp.35-42
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• 2017

The purpose of the present study was to explore the features of Emotional Intelligence(EI) in psychiatric patients in terms of the ability model. EI scores of patients, measured by performance-based test and self-report inventory, was compared. The scores of performance-based test(Emotional Literacy Test) and self-report inventory(Trait Meta-Mmood Scale) of patients(30 with psychotic symptoms, 32 without psychotic symptoms) who had a appropriate literacy were analyzed by means of independent t-test. There was a no significant difference of IQ between two groups. Our results indicated that psychotic group had significantly lower EI in performance-based test than non-psychotic group. In contrast, non-psychotic group showed lower EI in self-report inventory than psychotic group. This inconsistent results might be attributable to the differences in method of measurement. Thus, these results suggested that it may be important to adopt a convergent using of both performance-based test and self-report inventory while assessing EI of patients with psychopathology.