• Advances in nano research
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• v.6 no.4
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• pp.377-397
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• 2018

In the present investigation, thermal buckling and free vibration characteristics of functionally graded (FG) Timoshenko nanobeams subjected to nonlinear thermal loading are carried out by presenting a Navier type solution. The thermal load is assumed to be nonlinear distribution through the thickness of FG nanobeam. Thermo-mechanical properties of FG nanobeam are supposed to vary smoothly and continuously throughout the thickness based on power-law model and the material properties are assumed to be temperature-dependent. Eringen's nonlocal elasticity theory is exploited to describe the size dependency of nanobeam. Using Hamilton's principle, the nonlocal equations of motion together with corresponding boundary conditions based on Timoshenko beam theory are obtained for the thermal buckling and vibration analysis of graded nanobeams including size effect. Moreover, in following a parametric study is accompanied to examine the effects of the several parameters such as nonlocal parameter, thermal effect, power law index and aspect ratio on the critical buckling temperatures and natural frequencies of the size-dependent FG nanobeams in detail. According to the numerical results, it is revealed that the proposed modeling can provide accurate frequency results of the FG nanobeams as compared some cases in the literature. Also, it is found that the small scale effects and nonlinear thermal loading have a significant effect on thermal stability and vibration characteristics of FG nanobeams.

• Nuclear Engineering and Technology
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• v.50 no.8
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• pp.1217-1233
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• 2018

Following a surge of interest in multi-unit risk in the last few years, many recent studies have suggested methods for multi-unit probabilistic safety assessment (MUPSA) and addressed several related aspects. Most of the existing studies though focused on two-unit nuclear power plant (NPP) sites or used rather simplified probabilistic safety assessment (PSA) models to demonstrate the proposed approaches. When considering an NPP site with three or more units, some approaches are inapplicable or yield very conservative results. Since the number of such sites is increasing, there is a strong need to develop and validate practical approaches to the related MUPSA. This article provides several detailed approaches that are applicable to multi-unit Level 1 PSA for sites with up to six or more reactor units. To validate the approaches, a multi-unit Level 1 PSA model is developed and the site core damage frequency is estimated for each of four representative multi-unit initiators, as well as for the case of a simultaneous occurrence of independent single-unit initiators in multiple units. For this purpose, an NPP site with six identical OPR-1000 units is considered, with full-scale Level 1 PSA models for a specific OPR-1000 plant used as the base single-unit models.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.547-559
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• 2022

For a chi-squared test, which is a statistical method used to test the independence of a contingency table of two factors, the expected frequency of each cell must be greater than 5. The percentage of cells with an expected frequency below 5 must be less than 20% of all cells. However, there are many cases in which the regional expected frequency is below 5 in general small area studies. Even in large-scale surveys, it is difficult to forecast the expected frequency to be greater than 5 when there is small area estimation with subgroup analysis. Another statistical method to test independence is to use the Bayes factor, but since there is a high ratio of data dependency due to the nature of the Bayesian approach, the low expected frequency tends to decrease the precision of the test results. To overcome these limitations, we will borrow information from areas with similar characteristics and pool the data statistically to propose a pooled Bayes test of independence in target areas. Jo et al. (2021) suggested hierarchical Bayesian pooling models for small area estimation of categorical data, and we will introduce the pooled Bayes factors calculated by expanding their restricted pooling model. We applied the pooled Bayes factors using bone mineral density and body mass index data from the Third National Health and Nutrition Examination Survey conducted in the United States and compared them with chi-squared tests often used in tests of independence.

• Steel and Composite Structures
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• v.48 no.4
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• pp.443-459
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• 2023

This paper investigates the stability of a bi-directional functionally graded (BD-FG) cylindrical beam made of imperfect concrete, taking into account size-dependency and the effect of geometry on its stability behavior. Both buckling and dynamic behavior are analyzed using the modified coupled stress theory and the classical beam theory. The BD-FG structure is created by using porosity-dependent FG concrete, with changing porosity voids and material distributions along the pipe radius, as well as uniform and nonuniform radius functions that vary along the beam length. Energy principles are used to generate partial differential equations (PDE) for stability analysis, which are then solved numerically. This study sheds light on the complex behavior of BD-FG structures, and the results can be useful for the design of stable cylindrical microstructures.

• Geomechanics and Engineering
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• v.28 no.5
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• pp.477-491
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• 2022

In the present study, the effects of thermal loading on the buckling and resonance frequency of graphene platelets (GPL) reinforced nano-composites are examined. Functionally graded (FG) material properties are considered in thickness direction for the thermal responses of the composite. The equivalent material properties are obtained using Halphin-Tsai nano-mechanical model for composite layers. Moreover, the effects of nano-scale sizes are taken into account, employing functionally modified couple stress (FMCS) parameter. In this regard, for the first time, it is demonstrated that at certain values of GPL weight fraction, thermal buckling occurs. In obtaining results of vibrational behavior, both analytical solution and deep neural network (DNN) methods are used. The DNN method needs low computational costs to predict the resonance behavior. A comprehensive parametric study is conducted to indicate the effects of several geometrical, material, and loading conditions on the vibrational and buckling behavior of cylindrical shell structures made of GPL-nanocomposites. It is shown that the effect of temperature change on the occurrence of buckling is vital while it has a negligible impact on the resonance frequency of the structure. Moreover, the size-dependency of the results is demonstrated, and it cannot be neglected in nano-scales.

• Membrane and Water Treatment
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• v.15 no.1
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• pp.1-9
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• 2024

Biological nutrient removal is gaining increasing attention in wastewater treatment plants; however, it is adversely affected by low temperatures. This study examined temperature effects on nutrient removal and morphological stability of the granular and denitrifying phosphorus accumulating organisms (PAO and DPAO, respectively) using sequencing batch reactors (SBRs) at 5, 10, and 20 ℃. Lab-scale SBRs were continuously operated using anaerobic-anoxic and anaerobic-oxic cycles to develop the PAO and DPAO granules for 230 d. Sludge granulation in the two SBRs was observed after approximately 200 d. The average removal efficiency of soluble chemical oxygen demand (SCOD) and PO₄^3--P remained >90% throughout, even when the temperature dropped to 5 ℃. The average removal efficiency of NO₃^--N remained >80% consistently in DPAO SBR. However, nitrification drastically decreased at 10 ℃. Hence, the removal efficiency of NH₄⁺-N was decreased from 99.1% to 54.5% in PAO SBR. Owing to the increased oxygen penetration depth at low temperatures, the influence on nitrification rates was limited. The granule in DPAO and PAO SBR was observed to be unstable and disintegrated at 10 ℃. In conclusion, morphological characteristics showed that changed conversion rates at low temperatures in aerobic granular sludge altered both nutrient removal efficiencies and granule formation.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.7 no.1
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• pp.92-109
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• 1996

The objectives of the present study were to provide comprehensive assessment of the impact of epilepsy on the psychological well-being of children with epilepsy and to identify the neurological factors associated with the psychopathology. The participant patients were recruited from the population of children and adolescent aged 7 to 16 attending the OPD of department of pediatric neurology in Seoul National University Hospital in Korea. We exclude mental retardation, pervasive developmental disorder and brain organic pathology. As control group, formal students were chosen and their sex, age, achievement, socioeconomic status were matched to patients. The first author interviewed the children and their family members and obtained the developmental history and family information. We used the following 10 scales for assessing psychological and behavioral problems in patients and their family member. The scales were standardized and their validity and reliability were confirmed before. Parent rating scales : Yale children's inventory, Disruptive behavior disorder scale, Parent's attitude to epilepsy questionnaire, Family environment scale, Symptom check-list-90 revision, Children behavior check-list. Children's self rating scales : Children's depression inventory, Spielberger's state-trait anxiety anxiety, Piers-Harris self-concept inventory and Self-administered Dependency questionnaire for Mother. The result showed the risk factors associated depression were early onset, complex partial seizure, lateralized temporal focal abnormality on EEG, Drug polypharmacy, high seizure frequency and sick factors associated anxiety were old age of patient, lateralized temporal focal abnormality EEG, Drug polypharmacy, high seizure frequency. Also the result of this present study indicated that risk factors associated oppositional defiant disorder, conduct disorder and attention deficit hyperactivity disorder were young age, male, early onset, lateral temporal EEG abnormality and high seizure frequency. According to these results, common risk factors associated psychological and behavioral problems were lateralized EEG temporal abnormality, high seizure frequency in neurological factors.

• Korean Journal of Culture and Social Issue
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• v.13 no.3
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• pp.23-63
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• 2007

The purpose of this study is to develop and verify the Relational Self Scale(RSS). Based on the theoretical assumptions which relational self is multi-dimensional and constructed in social contexts, 10 categories with 102 items were yielded. In the process of content analysis, item analysis, exploratory factor analysis and correlation analysis by administering 102 items to korean adults, 31 items with 7 factors are extracted. The 7 factors are consisted of 'avoidance of relation', 'consciousness of others', 'agency', 'instrumental relation', 'empathy-care', 'perceived support from relation' and 'over-dependency to relation'. Next, Confirmatory factor analysis was conducted with 649 korean adults aged from 20's to 60's. The results of confirmatory factor analysis showed the RSS as a valid scale. The 7 factors of the RSS fitted well with men and women. The internal consistency of the RSS was proved to be acceptable. The latent mean analysis indicated that the relational self was not significantly different between men and women at 7 factors. Correlation analysis showed that the construct of relational self was significantly related to relational self-construal, self-esteem and attachment to parent and intimacy person. This study has implication in that relational self is defined and assessed as multi-dimensional construct, and that by administering RSS it is possible to evaluate distinctive korean people's relational self.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.101-104
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• 2009

This study investigated compensatory mechanisms in the brain during a verbal working memory task among people with Alcohol Use Disorders (AUD). A total of 21 college male students participated in the study: eleven AUD participants and 10 normal controls. Study participants were asked to complete the Korean version of the Wechsler Adult Intelligence Scale-III (K-WAIS-III) prior to the fMRI experiment. Verbal 0-back and 2-back tasks were used to assess brain activities of the participants' verbal working memory. Brain scanning was performed on Siemens SONATA 1.5T Scanner while participants were performing the 0-back and 2-back tasks. Within the AUD group, participants with greater dependency to alcohol (based on DSM-IV criteria) in the past 1 year showed lower mean score on the 'Similarities' of the K-WAIS-III (r=-0.63, p<0.05, N=11). The more participants experienced alcohol withdrawal symptoms in the past 1 year, the lower the score they received on the K-WAIS-III 'Picture Arrangement' (r=-0.69, p<0.05, n=11). The fMRI regression results showed that individuals who present greater degree of alcohol dependency symptoms are likely to show greater brain activation in the bilateral middle frontal gyri (BA 9) during the verbal working memory task. The degree of alcohol withdrawal symptoms were associated with increased brain activation in the left superior and middle frontal gyri (BA8), left precentral gyrus (BA 6), and left inferior parietal lobule (BA 40). The study findings showed that the degree of alcohol abuse/dependence and withdrawal symptoms were associated with decreased cognitive function and increased activations in brain regions particularly important for abstract reasoning (BA 9), central executive (BA 9), or spatial storage (BA 40) during a working memory task. Therefore, these results could support previous studies suggesting that the neural system of people with ADD may adopt a brain compensatory mechanism to maintain normal level of cognitive functions.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.1-12
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• 2020

In the medical field, numerical imbalance of data due to differences in disease prevalence is a common problem. It reduces the performance of a artificial intelligence network, leading to difficulties in learning a network with good performance. Recently, generative adversarial network (GAN) technology has been introduced as a way to address this problem, and its ability has been demonstrated by successful applications in various fields. However, it is still difficult to achieve good results in solving problems with performance degraded by numerical imbalances because the image resolution of the previous studies is not yet good enough and the structure in the image is modeled locally. In this paper, we propose a multi-scale conditional generative adversarial network based on attention mechanism, which can produce high resolution images to solve the numerical imbalance problem of chest X-ray image data. The network was able to produce images for various diseases by controlling condition variables with only one network. It's efficient and effective in that the network don't need to be learned independently for all disease classes and solves the problem of long distance dependency in image generation with self-attention mechanism.