• ETRI Journal
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• v.33 no.5
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• pp.712-719
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• 2011

In this paper, we study the problem of domain adaptation for structural support vector machines (SVMs). We consider a number of domain adaptation approaches for structural SVMs and evaluate them on named entity recognition, part-of-speech tagging, and sentiment classification problems. Finally, we show that a prior model for structural SVMs outperforms other domain adaptation approaches in most cases. Moreover, the training time for this prior model is reduced compared to other domain adaptation methods with improvements in performance.

• Safety and Health at Work
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• v.14 no.2
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• pp.222-228
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• 2023

Background: This study aimed to explore relationships between job stress and psychological adaptation and how they related to interpersonal needs through mood states among female migrant manufacturing workers. Methods: A cross-sectional survey was conducted in 16 factories in Shenzhen, China. Sociodemographic, job stress, psychological adaptation and other psychological information of was collected. Structural equation modeling was performed to delineate the internal relationship between variables. Results: The hypothetical structural equation model exhibited acceptable model fit among female migrant manufacturing workers (χ² = 11.635, df = 2, χ²/df = 5.82, p = 0.003, RMSEA = 0.090, CFI = 0.972, SRMR = 0.020). Job stress was directly associated with mood states and interpersonal needs; Psychological adaptation was directly associated with mood states and indirectly associated with interpersonal needs; Bootstrapping tests demonstrated mediation effect of mood states in the way from psychological adaptation to interpersonal needs. Conclusion: Female migrant manufacturing workers who suffered stress from job and the process of psychological adaptation may have worse mood states and workers with worse mood states are more likely to develop unmet interpersonal needs, a proximal factor of suicidal ideation.

• Journal of the Korean Home Economics Association
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• v.40 no.9
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• pp.175-189
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• 2002

The purpose of this study was to test a structural model about family income as causally related to family hardiness, pile-up stress, communication, and family adaptation in families of children with disabilities. 250 families of children with disabilities participated as subjects. The models were developed on the basis of confirmatory factor analysis and compared using covariance structure modeling(LISREL). Adequate fitness of the model was observed. Family income showed negative effect on pile-up stress and positive effect on family adaptation. Pile-up stress showed negative effect on family hardiness. Family hardiness showed positive effect on family communication, and family communication showed positive effect on family adaptation.

• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.188-193
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• 2003

Regardless of the distribution of the adaptation data in the testing environment, model-based adaptation methods that have so far been reported in various literature incorporates the adaptation data undiscriminatingly in reducing the mismatch between the training and testing environments. When the amount of data is small and the parameter tying is extensive, adaptation based on outlier data can be detrimental to the performance of the recognizer. The distribution of the adaptation data plays a critical role on the adaptation performance. In order to maximally improve the recognition rate in the testing environment using only a small number of adaptation data, supervised weighted training is applied to the structural maximum a posterior (SMAP) algorithm. We evaluate the performance of the proposed weighted SMAP (WSMAP) and SMAP on TIDIGITS corpus. The proposed WSMAP has been found to perform better for a small amount of data. The general idea of incorporating the distribution of the adaptation data is applicable to other adaptation algorithms.

• Journal of Korean Academy of Nursing
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• v.40 no.1
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• pp.127-138
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• 2010

Purpose: This study was designed to develop and test a structural model for children's adaptation in divorced families. The hypothetical model was constructed based on the Family Resilience Model by McCubbin and McCubbin. Methods: Data were collected using self-report questionnaires from 219 children (3-6th grade) in divorced families. The children attended one of 22 community agencies, 8 after-school programs, 3 elementary schools in three cities in South Korea. The collected data were analyzed using LISREL program to test the hypothetical model. Results: The modified model was constructed by deleting four paths in accordance with the statistical and theoretical criteria. Compared to the hypothetical model, the revised one had a better fit to the data. Self-esteem, and beliefs about parental divorce had direct effects, and family communication and internal control had indirect effects on children's adaptation in divorced families. These variables explained 56% of the variance in children's adaptation. Conclusion: The modified model was supported by empirical data. This model could be applied to family nursing interventions with divorced families or any other suffering family transition. When working with children experiencing parental divorce, it is important for nurses to enhance children's self-esteem, family communication and to decrease children's negative beliefs about parental divorce to help in their adaptation.

• Phonetics and Speech Sciences
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• v.4 no.3
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• pp.111-117
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• 2012

In this paper, we compare the performance of several speaker adaptation methods for a HMM-based Korean speech synthesis system with small amounts of adaptation data. According to objective and subjective evaluations, a hybrid method of constrained structural maximum a posteriori linear regression (CSMAPLR) and maximum a posteriori (MAP) adaptation shows better performance than other methods, when only five minutes of adaptation data are available for the target speaker. During the objective evaluation, we find that the duration models are insufficiently adapted to the target speaker as the spectral envelope and pitch models. To alleviate the problem, we propose the duration rectification method and the duration interpolation method. Both the objective and subjective evaluations reveal that the incorporation of the proposed two methods into the conventional speaker adaptation method is effective in improving the performance of the duration model adaptation.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.351-356
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• 2023

This study was conducted to identify the structural causal relationship between the quality of college education service, college life adaptation, and learning competency perceived by undergraduate probation students. To achieve this research purpose, data were collected and analyzed through the development of questionnaires for undergraduate students and online questionnaires. The research results are as follows. First, it was found that university administrative service had a negatively significant effect on college life adaptation and learning competency. Second, it was found that the curriculum had a positive and significant effect on learning competencies through college life adaptation. Third, it was found that adaptation to college life had a statically significant effect on learning competency. These research results suggest that it is necessary to support the improvement of college life adaptation ability through the operation of university administrative services and curriculum tailored to students with academic probation.

• Journal of Ship and Ocean Technology
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• v.5 no.3
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• pp.27-35
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• 2001

In this research, hybrid method with case-based reasoning and rule-based reasoning is applied. Using case-based reasoning, design experts'experience and know-how are effectively represented in order to obtain a proper configuration of midship section in the initial ship design stage. Since there is not sufficient domain knowledge available to us, traditional case-adaptation algorithms cannot be applied to our problem, i.e., creating the configuration of midship section. Thus, new case-adaptation algorithms not requiring any domain knowledge are developed antral applied to our problem. Using the knowledge representation of DnV rules, rule-based reasoning can perform deductive inference in order to obtain the scantling of midship section efficiently. The results from the case-based reasoning and the rule-based reasoning are examined by comparing the results with various conventional methods. And the reasonability of our results is verified by comparing the results wish actual values from parent ship.

• The Journal of Information Systems
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• v.27 no.2
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• pp.135-155
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• 2018

Purpose Recently, with the enhancement of mobile technologies, people have formed various relationships and spreaded networks on social network service(SNS). In addition, although people make a decision based on the thoughts and emotions about self, there is little empirical research on social relations and self-construal of users in social network game (SNG). Design/methodology/approach This study was designed to examine the structural relationships among SNG users' social capital, self-construal, behavioral adaptation, SNG reuse intention and charged item purchasing intention. Findings The results from this study are as follow. First of all, the bonding social capital did not have a significant impact on behavioral adaptation to SNG, but bridging social capital had a positive impact on behavioral adaptation. Second, independent self-construal did not have a significant impact on behavioral adaptation to SNG, but interdependent self-construal had a positive impact on behavioral adaptation. Lastly, the behavioral adaptation to SNG had a positive impact reuse intention and charged item purchasing intention. Also, SNG reuse intention had a positive impact on charged item purchasing intention.

• ETRI Journal
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• v.36 no.3
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• pp.429-438
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• 2014

Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.