• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.605-618
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• 2022

Glass fiber reinforced polymer (GFRP) elastic gridshells consist of long continuous GFRP tubes that form elastic deformations. In this paper, a method for the form-finding of gridshell structures is presented based on the interpretable machine learning (ML) approaches. A comparative study is conducted on several ML algorithms, including support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), AdaBoost, XGBoost, category boosting (CatBoost), and light gradient boosting machine (LightGBM). A numerical example is presented using a standard double-hump gridshell considering two characteristics of deformation as objective functions. The combination of the grid search approach and k-fold cross-validation (CV) is implemented for fine-tuning the parameters of ML models. The results of the comparative study indicate that the LightGBM model presents the highest prediction accuracy. Finally, interpretable ML approaches, including Shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions of the ML model since it is essential to understand the effect of various values of input parameters on objective functions. As a result of interpretability approaches, an optimum gridshell structure is obtained and new opportunities are verified for form-finding investigation of GFRP elastic gridshells during lifting construction.

• Human Ecology Research
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• v.55 no.3
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• pp.275-287
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• 2017

The recent Great Recession of 2008 was a period of sharp economic decline throughout the late 2000s. All socio-demographic groups were impacted by the economic downturn, however, Hispanic households were particularly hard hit. It is not a recent phenomenon that minority groups often have greater problems related to credit and debt repayments. A better understanding of these racial/ethnic differences in credit and debt has been hindered by the propensity of many studies to pool all racial/ethnic minorities together and compare them to white households. Using a Heckman-type selection model with a combination of the 2010 and 2013 Survey of Consumer Finances datasets to study household debt repayment problems, we found that racial/ethnic groups have been differently impacted by the recent Great Recession in terms of debt repayment problems. Hispanic households were less likely to hold debt; however, those with debt were just as likely as white households and African American households to be delinquent in repayments. This finding is contrary to prior research that indicated Hispanics with debt were less likely than white and African American households to be delinquent on repayments prior to the Great Recession of 2008. We propose possible explanations for the increase in debt repayment problems, that includes increased assimilation into the U.S. culture of credit use, the circumstance of being more recent home buyers prior to the decline, and living in states that suffered the greatest decline in housing value.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.363-370
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• 2022

The study aims to probe the impact of foreign ownership on Vietnamese listed firms' capital structure. This study employs panel data of 288 non-financial firms listed on the Ho Chi Minh City stock exchange (HOSE) and Ha Noi stock exchange (HNX) in 2015-2019. In this research, we applied a Bayesian linear regression method to provide probabilistic explanations of the model uncertainty and effect of foreign ownership on the capital structure of non-financial listed enterprises in Vietnam. The findings of experimental analysis by Bayesian linear regression method through Markov chain Monte Carlo (MCMC) technique combined with Gibbs sampler suggest that foreign ownership has substantial adverse effects on the firms' capital structure. Our findings also indicate that a firm's size, age, and growth opportunities all have a strong positive and significant effect on its debt ratio. We found that the firms' profitability, tangible assets, and liquidity negatively and strongly affect firms' capital structure. Meanwhile, there is a low negative impact of dividends and inflation on the debt ratio. This research has ramifications for business managers since it improves a company's financial resources by developing a strong capital structure and considering foreign investment as a source of funding.

• Childhood Kidney Diseases
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• v.16 no.1
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• pp.9-14
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• 2012

The relationship between central nervous system (CNS) and enuresis has not been sufficiently elucidated despite the presence of several circumstantial evidences. Contrary to common belief, polysomnographic sleep analysis revealed that the disturbance of arousal rather than deep sleep was responsible for enuresis. Subsequent studies confirmed depressed sympathetic tone and retarded brainstem reflex indicating abnormal arousal threshold in enuretics. In accordance with the bladder-brain dialogue, chronic stimulation of bladder may modify the brainstem function elevating arousal threshold. Epidemiological studies have suggested the association between enuresis and various psychosomatic disorders like attention deficit hyperactivity disorder (ADHD), which has shown the abnormal brainstem reflex similar to enuresis. Taken together, CNS is assumed to play a crucial role in the pathogenesis of enuresis. Psychological assessment is vital to understand the psychodynamic effect of enuresis. Studies have shown that the prevalence of psychological problems was higher in enuretic children and externalization of the symptoms was usually found. Several explanations have been brought up regarding the development of enuresis and psychological problems. Enuresis may cause psychological problems and vice versa. Otherwise, both may be associated with other variables, such as socioeconomic status (SES).

• Journal of The Korean Astronomical Society
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• v.46 no.6
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• pp.235-242
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• 2013

We compare mass-loss rates of OH/IR stars obtained from radio observations with those derived from the dust radiative transfer models and IR observations. We collect radio observational data of OH maser and CO line emission sources for a sample of 1533 OH/IR stars listed in Suh & Kwon (2011). For 1259 OH maser, 76 CO(J=1-0), and 55 CO(J=2-1) emission sources, we compile data of the expansion velocity and mass-loss rate. We use a dust radiative transfer model for the dust shell to calculate the mass-loss rate as well as the IR color indices. The observed mass-loss rates are in the range predicted by the theoretical dust shell models corresponding to $\dot{M}=10^{-8}M_{\odot}/yr-10^{-4}M_{\odot}/yr$. We find that the dust model using a simple mixture of amorphous silicate and amorphous $Al_2O_3$ (20% by mass) grains can explain the observations fairly well. The results indicate that the dust radiative transfer models for IR observations generally agree with the radio observations. For high mass-loss rate OH/IR stars, the mass-loss rates obtained from radio observations are underestimated compared to the mass-loss rates derived from the dust shell models. This could be because photon momentum transfer to the gas shell is not possible for the physical condition of high mass-loss rates. Alternative explanations could be the effects of different dust-to-gas ratios and/or a superwind.

• Journal of Contemporary Eastern Asia
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• v.13 no.2
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• pp.15-39
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• 2014

This research conducted a before/after naturalistic field experiment, with the early Arab Spring as the treatment. Compared to before the early Arab Spring, after the observation period the associations became stronger among the Web terms: 'Jihad, Sharia, innovation, democracy and civil society.' The Western concept of civil society transformed into a central Islamist ideological component. At another level, the inter-nation network based on Jihad-weighted Web hyperlinks between pairs of 46 Muslim Majority (MM) nations found Iran in one of the top two positions of flow betweenness centrality, a measure of network power, both before and after early Arab Spring. In contrast, Somalia, UAE, Egypt, Libya, and Sudan increased most in network flow betweenness centrality. The MM 'Jihad'-centric word co-occurrence network more than tripled in size, and the semantic structure more became entropic. This media "cloud" perhaps billowed as Islamist groups changed their material-level relationships and the corresponding media representations of Jihad among them changed after early Arab Spring. Future research could investigate various rival explanations for this naturalistic field experiment's findings.

• Cartoon and Animation Studies
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• s.11
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• pp.87-104
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• 2007

This paper proposes to analyze artistic characteristic based on the line expression of , Te Wei's Chinese water-ink animation. We considered the transitions of Chinese water-ink animation through Shang-hai Animation Film Studio's works which induced the dominant improvement in Chinese animations and other major animation industries internationally with the theoretical explanations about particular understanding of line concept and formative characteristics. We not only considered line expression of , aesthetic and idea etc. which are the central point of this paper but also researched the artistic possibilities through the effects of Chinese water ink and line and the relationship of animation.

• Korean journal of communication and information
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• v.48
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• pp.191-210
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• 2009

In this study, we examined the influence of news frame and involvement on risk perception. Based on individuals' optimistic bias in risk judgement and the third-person effect theory, we developed research hypotheses. An experiment was conducted in which 243 undergraduate and graduate students participated. Results indicated that societal level risk judgements were relatively invariant across experimental conditions but personal level risk judgements were influenced by the news frame and individuals' involvement in irradiated food. Based on the results, we provide explanations concerning when and how optimistic bias takes place in each experimental condition.

• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.985-997
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• 2004

In this paper, an automatic programming error-diagnosing system is provided for novice C programmers by plan matching and program execution. Program execution results are used to provide flexibility in describing the relationship between programming plans, to verify the correctness of the plan matching differences, and to detect the influence of a plan's error to the related plan. We can give easy and informative explanations to the students according to a plan's error and the resulting effects to related plans. The students are consulted to check their program's correctness with the given test data. Our error-diagnosing system is tested with student's programs for the 14 various and difficult problems and gives acceptable recognition results.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.1-11
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• 2021

As the Internet developed, various and complex cyber attacks began to emerge. Various detection systems were used outside the network to defend against attacks, but systems and studies to detect attackers inside were remarkably rare, causing great problems because they could not detect attackers inside. To solve this problem, studies on the lateral movement detection system that tracks and detects the attacker's movements have begun to emerge. Especially, the method of using the Remote Desktop Protocol (RDP) is simple but shows very good results. Nevertheless, previous studies did not consider the effects and relationships of each logon host itself, and the features presented also provided very low results in some models. There was also a problem that the model could not explain why it predicts that way, which resulted in reliability and robustness problems of the model. To address this problem, this study proposes an interpretable RDP-based lateral movement detection system using page rank algorithm and SHAP(Shapley Additive Explanations). Using page rank algorithms and various statistical techniques, we create features that can be used in various models and we provide explanations for model prediction using SHAP. In this study, we generated features that show higher performance in most models than previous studies and explained them using SHAP.