• English & American cultural studies
• /
• v.17 no.1
• /
• pp.27-54
• /
• 2017

Brian Ascalon Roley's American Son, one of the outstanding Filipino American novels after the LA riots, critically deals with a racial issue of his community which has been intermingled with the myth of model minority. Gabe and Thomas, considered as obedient Filipino younger immigrants, are asked to achieve the American dream as a way to place themselves at the center of the mainstream white society. However, they recognize that they cannot be accepted as a suitable subject for the invincible racism deeply rooted in the society. While Tomas refuses to become a model minority by identifying himself with the Mexican, Gabe is expected to become an idealistic subject of model minority by his mother since he complies with the rules of the mainstream society. However, he accepts his brother's violent way of life in that violence is necessary to protect his family from the racial discrimination in America. Though he is his mother's hope for model minority, he recognizes the only condition to achieve her expectation is the American society where there is no racism at all. However, by taking the case of Gabe and Thomas, Roley suggests that the younger generation of Filipino American immigrants have no choice but to accept violence to survive in the American society because racism always threatens their life.

• Geomechanics and Engineering
• /
• v.29 no.3
• /
• pp.301-310
• /
• 2022

Accurate prediction of mixed ground conditions ahead of a tunnel face is of vital importance for safe excavation using tunnel boring machines (TBMs). Previous studies have primarily focused on electrical resistivity surveys from the ground surface for geotechnical investigation. In this study, an FE (finite element) numerical model was developed to simulate electrical resistivity surveys for the prediction of risky mixed ground conditions in front of a tunnel face. The proposed FE model is validated by comparing with the apparent electrical resistivity values obtained from the analytical solution corresponding to a vertical fault on the ground surface (i.e., a simplified model). A series of parametric studies was performed with the FE model to analyze the effect of geological and sensor geometric conditions on the electrical resistivity survey. The parametric study revealed that the interface slope between two different ground formations affects the electrical resistivity measurements during TBM excavation. In addition, a large difference in electrical resistivity between two different ground formations represented the dramatic effect of the mixed ground conditions on the electrical resistivity values. The parametric studies of the electrode array showed that the proper selection of the electrode spacing and the location of the electrode array on the tunnel face of TBM is very important. Thus, it is concluded that the developed FE numerical model can successfully predict the presence of a mixed ground zone, which enables optimal management of potential risks.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.22 no.4
• /
• pp.111-117
• /
• 2022

Many studies have been conducted on software fault prediction models for decades, and the models using machine learning techniques showed the best performance. Deep learning techniques have become the most popular in the field of machine learning, but few studies have used them as classifiers for fault prediction models. Some studies have used deep learning to obtain semantic information from the model input source code or syntactic data. In this paper, we produced several models by changing the model structure and hyperparameters using MLP with three or more hidden layers. As a result of the model evaluation experiment, the MLP-based deep learning models showed similar performance to the existing models in terms of Accuracy, but significantly better in AUC. It also outperformed another deep learning model, the CNN model.

• Journal of Electrical Engineering and Technology
• /
• v.11 no.2
• /
• pp.405-415
• /
• 2016

This paper presents a model predictive control for shunt active power filters in synchronous reference frame using space vector pulse-width modulation (SVPWM). The three phase load currents are transformed into synchronous rotating reference frame in order to reduce the order of the control system. The proposed current controller calculates reference current command for harmonic current components in synchronous frame. The fundamental load current components are transformed into dc components revealing only the harmonics. The predictive current controller will add robustness and fast compensation to generate commands to the SVPWM which minimizes switching frequency while maintaining fast harmonic compensation. By using the model predictive control, the optimal switching state to be applied to the next sampling time is selected. The filter current contains only the harmonic components, which are the reference compensating currents. In this method the supply current will be equal to the fundamental component of load current and a part of the current at fundamental frequency for losses of the inverter. Mathematical analysis and the feasibility of the suggested approach are verified through simulation results under steady state and transient conditions for non-linear load. The effectiveness of the proposed controller is confirmed through experimental validation.

• Computers and Concrete
• /
• v.8 no.6
• /
• pp.717-733
• /
• 2011

Strengthening of reinforced concrete (RC) members against shear that is one of the failure modes especially avoided by using carbon fiber reinforced polymer (CFRP) is widely used technique, which is studied at many experimental studies. However, conducting experimental studies are required more financial resources and laboratory facilities. In addition, along with financial resources, more time is needed in order to carry out comprehensive experimental studies. For these reasons, a verified finite element model that is tested with previous experimental studies can be used for reaching generalized results and investigating parameters that are not studied. For this purpose, previous experimental study results are used and "T" cross-sectioned RC beams strengthened with CFRP strips with insufficient shear strength are modeled by using ANSYS software. First, finite elements modeling of the previously tested RC beams are done, and then the computed results are compared with the experimental ones whether they are matched or not. As a result, the finite element model is verified. Later, analyses of the cases without any test results are done by using the verified model. Optimum CFRP strip spacing is determined with this verified finite element model, and compared with the experimental findings.

• Safety and Health at Work
• /
• v.1 no.1
• /
• pp.37-42
• /
• 2010

Over years it has been increasingly concerned with how upper extremity musculoskeletal disorders (UEMSDs) are attributed to psychosocial job stressors. A review study was conducted to examine associations between UEMSDs and psychosocial work factors, and to recommend what to consider for the associations. For studies in which the job demand-control-support (DCS) model or its variables were specifically employed, published papers were selected and reviewed. A number of studies have reported relationships between UEMSDs symptoms and psychosocial exposure variables. For example, the findings are: higher numbness in the upper extremity was significantly attributed to by less decision latitude at work; work demands were significantly associated with neck and shoulder symptoms while control over time was associated with neck symptoms; and the combination of high psychosocial demands and low decision latitude was a significant predictor for shoulder and neck pain in a female working population. Sources of bias, such as interaction or study design, were discussed. UEMSDs were shown to be associated with psychosocial work factors in various studies where the job DCS model was addressed. Nonetheless, this review suggests that further studies should be conducted to much more clarify the association between UEMSDs and psychosocial factors.

• International journal of steel structures
• /
• v.18 no.5
• /
• pp.1497-1507
• /
• 2018

Most of previous studies on fire resistance of restrained steel beams neglected creep effect due to lack of suitable creep model. This paper presents a finite element model (FEM) for accessing the fire resistance of restrained high strength Q460 steel beams by taking high temperature Norton creep model of steel into consideration. The validation of the established model is verified by comparing the axial force and deflection of restrained beams obtained by finite element analysis with test results. In order to explore the creep effect on fire response of restrained Q460 steel beams, the thermal axial force and deflection of the beams are also analyzed excluding creep effect. Results from comparison infer that creep plays a crucial role in fire response of restrained steel beam and neglecting the effect of creep may lead to unsafe design. A set of parametric studies are accomplished by using the calibrated FEM to evaluate the governed factors influencing fire response of restrained Q460 steel beams. The parametric studies indicate that load level, rotational restraint stiffness, span-depth ratio, heating rate and temperature distribution pattern are key factors in determining fire resistance of restrained Q460 steel beam. A simplified design approach to determine the moment capacity of restrained Q460 steel beams is proposed based on the parametric studies by considering creep effect.

• Journal of Korean Academy of Nursing
• /
• v.33 no.8
• /
• pp.1127-1134
• /
• 2003

Background. Although there have been a great number of research studies based on the model of uncertainty in illness, few studies have considered the appraisal portion of model. Purpose. The purpose of this study was to test the mediating effect of appraisal in the model of uncertainty in illness. Additionally, this study aimed to examine the relationships among uncertainty, symptom severity, appraisal, and anxiety in patients newly diagnosed with atrial fibrillation. Methods. This study employed a descriptive correlational and cross-sectional survey design using a face-to-face interview method. Patients diagnosed with atrial fibrillation within the previous 6 months prior to data collection were interviewed by Mishel Uncertainty in Illness Scale-Community Form, appraisal scale, Symptom Checklist-Severity V.3, and State Anxiety Inventory. Results. A total of 81 patients with atrial fibrillation were recruited from two large urban medical centers in Cleveland, Ohio, U.S.A.. Symptom severity was the significant variable in explaining uncertainty ($\beta$=0.34). Individuals with greater symptom severity perceived more uncertainty. Uncertainty was appraised as a danger rather than opportunity, and those with greater uncertainty appraised a greater danger (p<.0l). While the appraisal of opportunity had the negative relationship with anxiety (r=-0.25), the appraisal of danger was positively associated with anxiety (r=0.78). The measure of goodness of fit (Q) of the model was .7863, and the significant test (X$^2$) for the Q was statistically significant (df =3, p<.00l). Accordingly, the overall mediating model of uncertainty in illness was proven not to be fit to the empirical data of patients with atrial fibrillation. Consequently, the mediating effect of appraisal was not supported by the empirical data of this study. Conclusion. The findings of this study were discussed in terms of their relevance compared with those of previous studies or theoretical framework and the plausible explanations on study findings. Lastly, in order to expand the present body of knowledge on uncertainty in illness model, recommendations for the future nursing studies were included.

• Journal of Animal Environmental Science
• /
• v.16 no.1
• /
• pp.29-40
• /
• 2010

The purpose of the study is to review current studies for economic values on livestock products produced by animal welfare. In order to review the topic, published research papers and reports were reviewed in the world. As the result of the study, the studies for the topic are not researched actively. The main ideas for the studies were consumer survey on meats and egg. Data were questionnaire, Lexis-Nexis databases, consumptions and prices on meats, auction data. Tools for analyses were Random parameters logit and latent class model, WTP analysis, Roterdam model, Pearson's Chi test, Mann-Whitney V-test, Kruskal-Wallis test, structural equation model, regression model, Target-costing, and conjoint analysis.

• Electronics and Telecommunications Trends
• /
• v.35 no.3
• /
• pp.9-19
• /
• 2020

Recently, a technique for applying a deep learning language model pretrained from a large corpus to fine-tuning for each application task has been widely used as a language processing technology. The pretrained language model shows higher performance and satisfactory generalization performance than existing methods. This paper introduces the major research trends related to deep learning pretrained language models in the field of language processing. We describe in detail the motivations, models, learning methods, and results of the BERT language model that had significant influence on subsequent studies. Subsequently, we introduce the results of language model studies after BERT, focusing on SpanBERT, RoBERTa, ALBERT, BART, and ELECTRA. Finally, we introduce the KorBERT pretrained language model, which shows satisfactory performance in Korean language. In addition, we introduce techniques on how to apply the pretrained language model to Korean (agglutinative) language, which consists of a combination of content and functional morphemes, unlike English (refractive) language whose endings change depending on the application.