• ETRI Journal
• /
• v.35 no.1
• /
• pp.89-99
• /
• 2013

The problem of the sentence-based pronunciation evaluation task is defined in the context of subjective criteria. Three subjective criteria (that is, the minimum subjective word score, the mean subjective word score, and first impression) are proposed and modeled with the combination of word-based assessment. Then, the subjective criteria are approximated with objective sentence pronunciation scores obtained with the combination of word-based metrics. No a priori studies of common mistakes are required, and class-based language models are used to incorporate incorrect and correct pronunciations. Incorrect pronunciations are automatically incorporated by making use of a competitive lexicon and the phonetic rules of students' mother and target languages. This procedure is applicable to any second language learning context, and subjective-objective sentence score correlations greater than or equal to 0.5 can be achieved when the proposed sentence-based pronunciation criteria are approximated with combinations of word-based scores. Finally, the subjective-objective sentence score correlations reported here are very comparable with those published elsewhere resulting from methods that require a priori studies of pronunciation errors.

• The Journal of Fisheries Business Administration
• /
• v.46 no.3
• /
• pp.51-61
• /
• 2015

The purpose of this study is to find food safety approach in the Eco-label Chain of Custody(CoC) which is only focused to traceability. Because, consumers want to be assured the certified seafood comes from sustainable fishery as well as hygienic. In order to this approach, we used Analytic Hierarchy Process(AHP) method as belows. We first understood the CoC criteria for using pair-wise comparison and analyzed and selected each Eco-label certifications and standards. Second, we carried out a survey to the targeted standard Marine Stewardship Council(MSC) CoC auditors all over the world and analyzed the priorities of food safety approach to 4 principles and 12 criteria belong the MSC CoC Standard. As the results, we found out that 'Management System' has the highest priority in the principles and 'Documentation' and 'Keeping Record' are the most important criteria for this approach. In addition, 'Training' and 'Identification' are also higher priority of criteria. So, we suggested food safety approach method for improvement of these criteria in conclusion based on discussion with specialist in this field.

• Journal of Korean language education
• /
• v.28 no.1
• /
• pp.173-196
• /
• 2017

Writing is a subjective and performative activity. Writing ability has multi-facets and compoundness. To understand the examinees's writing ability accurately and provide effective writing scores, raters first ought to have the competency regarding assessment. Therefore, this study is significant as a fundamental research about rater's characteristics on the TOPIK writing assessment. 150 scripts of the 47th TOPIK examinees were selected randomly, and were further rated independently by 20 raters. The many-facet Rasch model was used to generate individualized feedback reports on each rater's relative severity and consistency with respect to particular categories of the rating scale. This study was analyzed using the FACETS ver 3.71.4 program. Overfit and misfit raters showed many difficulties for noticing the difference between assessment factors and interpreting the criteria. Writing raters appear to have much confusion when interpreting the assessment criteria, and especially, overfit and misfit teachers interpret the criteria arbitrarily. The main reason of overfit and misfit is the confusion about assessment factors and criteria in finding basis for scoring. Therefore, there needs to be more training and research is needed for raters based on this type of writing assessment characteristics. This study is recognized significantly in that it collectively examined writing assessment characteristics of writing raters, and visually confirmed the assessment error aspects of writing assessment.

• Journal of Oriental Neuropsychiatry
• /
• v.29 no.2
• /
• pp.79-97
• /
• 2018

Objectives: The purpose of this systematic review was to investigate the clinical effects of neurofeedback training on reducing anxiety. Methods: Eight databases were used to extract clinical reports on neurofeedback intervention for anxiety reduction published until 2016. We analyzed the characteristics of selected studies and evaluated biases using the Risk of Bias (RoB) assessment. Results: A total of 22 clinical trials were extracted for the analysis. The risk of bias in most studies was high or unclear. The Chinese Classification of Mental Disorders-3 (CCMD-3) was the most frequently used diagnostic criteria, the Hamilton Rating Scale for Anxiety (HAMA) was the most frequently used assessment tool, and the alpha wave activity increase, sensorimotor rhythm (SMR), and theta wave training were the most frequently used intervention methods. All papers showed a statistically significant decrease of anxiety symptoms; however, significant adverse events were not reported. Conclusions: Neurofeedback intervention might be beneficial for reducing anxiety. However, the quality of the studies used in the analysis was low, and the heterogeneity of the population and interventions was revealed. Therefore, more scientifically designed clinical studies regarding neurofeedback training are required.

• Nuclear Engineering and Technology
• /
• v.54 no.8
• /
• pp.3027-3033
• /
• 2022

Background: In this study, various types of deep-learning models for predicting in vitro radiosensitivity from gene-expression profiling were compared. Methods: The clonogenic surviving fractions at 2 Gy from previous publications and microarray gene-expression data from the National Cancer Institute-60 cell lines were used to measure the radiosensitivity. Seven different prediction models including three distinct multi-layered perceptrons (MLP), four different convolutional neural networks (CNN) were compared. Folded cross-validation was applied to train and evaluate model performance. The criteria for correct prediction were absolute error < 0.02 or relative error < 10%. The models were compared in terms of prediction accuracy, training time per epoch, training fluctuations, and required calculation resources. Results: The strength of MLP-based models was their fast initial convergence and short training time per epoch. They represented significantly different prediction accuracy depending on the model configuration. The CNN-based models showed relatively high prediction accuracy, low training fluctuations, and a relatively small increase in the memory requirement as the model deepens. Conclusion: Our findings suggest that a CNN-based model with moderate depth would be appropriate when the prediction accuracy is important, and a shallow MLP-based model can be recommended when either the training resources or time are limited.

• Physical Therapy Rehabilitation Science
• /
• v.13 no.3
• /
• pp.324-331
• /
• 2024

Objective: This study aimed to explore the effects of a novel training program that integrates ultrasound technology to enhance the palpation skills of physical therapy students. The program was designed to support students in developing more precise palpation techniques by using ultrasound as a supplementary tool for anatomical identification. Design: A randomized controlled trial. Methods: A total of twenty students, all enrolled in the physical therapy department at S University, who met the specified selection criteria, were randomly assigned to one of two groups: the experimental group (EG, n=10) or the control group (CG, n=10). The experimental group participated in an ultrasound-assisted palpation training program, while the control group did not receive this intervention. Results:The experimental group demonstrated significant improvements in their ability to accurately palpate anatomical landmarks, specifically the long head of the biceps brachii (LHBT) and the lateral joint line of the knee (LJLK), as well as an increased level of confidence in their palpation skills (p<0.05). A comparative analysis of changes from pre- to post-training revealed statistically significant differences between the two groups (p<0.05). Conclusions: The findings of this study suggest that the ultrasound-assisted training program can provide valuable educational benefits, offering foundational data to enhance the development of palpation skills in physical therapy students and making a meaningful contribution to educational research within the field.

• Journal of Korean Home Economics Education Association
• /
• v.21 no.4
• /
• pp.105-125
• /
• 2009

This study attempts to extract the necessary criteria as a secondary school home economics teacher through the factor analysis, and to analysis the teacher's and student's perceptions for the requirement criteria of home economics teacher(RCHET) thereof to confirm the necessary criteria as a secondary school home economics teachers. This research was based on the requirement criteria of home economics teacher developed by Korea Institute for Curriculum and Evaluation(KICE) Korean Home Economics Education Association(2008)(KHEEA) collected from secondary, upper secondary school home economics teachers and students in Jeollabuk-do. RCHET encompasses the six areas : (l)'Expert of lesson related to evaluation' (2)'Efficient manager of diverse materials for study', (3)'Student advisor equipped with a teaching sense of duty and sound humanity', (4)'Curriculum expert equipped with a expertise knowledge', (5)'A fair and democratic schoolroom environment promoter'. (6)'Career path counselling expert understanding student's characteristics and environments'. Through the factor analysis, six RCHET factors are more important to teachers than students. According to importance perception for RCHET, home economics teachers' qualification for minor second subject and participation of training program showed similar differences statistically in all RCHET factors. Thus, effort for expertise improvement of teacher had important influence on expertise improvement of teacher. As a result of examining the differences from importance evaluation for RCHET, similar differences from frequence of home project, preference of home economics teacher, manual training and home economics score, interest of home economics showed statistically.

• Clinical and Experimental Reproductive Medicine
• /
• v.51 no.1
• /
• pp.1-12
• /
• 2024

This review article discusses the integration of artificial intelligence (AI) in assisted reproductive technology and provides key concepts to consider when introducing AI systems into reproductive medicine practices. The article highlights the various applications of AI in reproductive medicine and discusses whether to use commercial or in-house AI systems. This review also provides criteria for implementing new AI systems in the laboratory and discusses the factors that should be considered when introducing AI in the laboratory, including the user interface, scalability, training, support, follow-up, cost, ethics, and data quality. The article emphasises the importance of ethical considerations, data quality, and continuous algorithm updates to ensure the accuracy and safety of AI systems.

• Journal of the Korean Data and Information Science Society
• /
• v.12 no.2
• /
• pp.113-124
• /
• 2001

CHAID, logistic regression, bagging trees, and bagging trees are compared on SAS artificial data set as HMEQ in terms of classification accuracy and training time. In error rates, bagging trees is at the top, although its run time is slower than those of others. The run time of logistic regression is best among given models, but there is no uniformly efficient model satisfied in both criteria.

• International Journal of Advanced Culture Technology
• /
• v.12 no.3
• /
• pp.206-212
• /
• 2024

This study presents five selection rules for training algorithms to extract audio sources from noise. The five rules are Dynamics, Roots, Tonal Balance, Tonal-Noisy Balance, and Stereo Width, and the suitability of each rule for sound extraction was determined by spectrogram analysis using various types of sample sources, such as environmental sounds, musical instruments, human voice, as well as white, brown, and pink noise with sine waves. The training area of the algorithm includes both melody and beat, and with these rules, the algorithm is able to analyze which specific audio sources are contained in the given noise and extract them. The results of this study are expected to improve the accuracy of the algorithm in audio source extraction and enable automated sound clip selection, which will provide a new methodology for sound processing and audio source generation using noise.