• Journal of Sport and Applied Science
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• v.8 no.2
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• pp.13-18
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• 2024

Purpose: The purpose of this study is to determine the effects of a 6-week weight training and complex training program on the Y-balance test (YBT) in high school soccer players. Research design, data, and methodology: This study included 26 high school soccer players from City S. Subjects were divided into a weight training group (WTG: n=13) and a complex training group (CTG: n=13) based on their willingness to participate without medical problems. The YBT measured anterior (AT), posteromedial (PM), posterolateral (PL), and composite scores (CS), and was measured twice: before the start and after the end of training. The data were analyzed using the SPSS 25.0 statistical program to compare pre- and post-training using paired-t tests, between training groups using independent-t tests, and left-right comparisons using independent-t tests. Results: Training resulted in a significant pre- to post-training change in PL in the left foot WTG group (p<.05), with no significant change in the other measures. There were no significant differences between training groups and between left and right sides. Conclusion: To improve YBT in high school soccer players, a program to improve ankle and hip mobility and strength should be added along with improving large muscle strength through weights and comflex training.

• The Journal of the Korea Contents Association
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• v.15 no.5
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• pp.78-87
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• 2015

An actor should be well-trained at the natural breathing and phonation in order for a good diction. This thesis is focused on the breathing training method at the pre-phonation stage. The past research on the breathing and phonation training was generally for vocal music, yoga, or those which were approached by the medical view point, whereas there are not so many researches which are approached for an acting training even though it is quite important for actors. In addition, such researches have been given an overview of breathing, phonation and diction. Therefore, this thesis which is focused on the breathing training at the pre-phonation stage suggests the natural breathing training method through the imagination and image in the various situations which could exist in the drama.

• The Journal of Korean Physical Therapy
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• v.27 no.5
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• pp.364-368
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• 2015

Purpose: Walking in the dual-task condition is a critical skill for hemiplegic patients to live in real-life situations. The purpose of this study was to compare the effect of dual-task gait training and general gait training on gait parameters and cognitive function in patients with chronic stroke during dual-task walking. Methods: The study included 23 patients with chronic hemiparetic stroke who were randomly divided into experimental (dual-task gait training) and control (general walking training) groups. The 11 subjects in the experimental group and nine subjects in the control group received dual-task gait training (walking while handling a ball, crossing obstacles, picking up various objects, and problem solving simple cognitive tasks and general over-ground gait training, respectively, for 30 minutes per day 5 days per week for 4 weeks. Spatiotemporal parameters and cognitive tasks in the dual-task gait condition were measured. Statistical analysis of the changes between the pre- and post-intervention measurement variables was performed using ANCOVA. Results: In the gait condition under cognitive tasks, the changes pre- and post-intervention in gait velocity, stride length, double support limb, and step symmetry were significantly greater in the dual-task gait training group; however, the dual-task gait training group showed no significant improvement compared to the general gait training group in terms of the assessment of cognitive tasks. Conclusion: The findings suggest that dual-task gait training may be beneficial for walking ability in dual-task walking condition.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.15-23
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• 2022

In the field of patents, as NLP(Natural Language Processing) is a challenging task due to the linguistic specificity of patent literature, there is an urgent need to research a language model optimized for Korean patent literature. Recently, in the field of NLP, there have been continuous attempts to establish a pre-trained language model for specific domains to improve performance in various tasks of related fields. Among them, ELECTRA is a pre-trained language model by Google using a new method called RTD(Replaced Token Detection), after BERT, for increasing training efficiency. The purpose of this paper is to propose KorPatELECTRA pre-trained on a large amount of Korean patent literature data. In addition, optimal pre-training was conducted by preprocessing the training corpus according to the characteristics of the patent literature and applying patent vocabulary and tokenizer. In order to confirm the performance, KorPatELECTRA was tested for NER(Named Entity Recognition), MRC(Machine Reading Comprehension), and patent classification tasks using actual patent data, and the most excellent performance was verified in all the three tasks compared to comparative general-purpose language models.

• The Mathematical Education
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• v.42 no.4
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• pp.523-540
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• 2003

The main purpose of this work is to propose programs of calculus for the department of mathematics education of teacher training universities. There is a description of the characteristics, goal and contents of calculus course for pre-service teacher, followed by principles for teaching the subject. We suggest the constituents and something being kept in mind for each part in calculus.

• The Mathematical Education
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• v.42 no.4
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• pp.579-588
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• 2003

The main purpose of this work is to propose programs of discrete mathematics for the department of mathematics education of teacher training universities. There is a description of the characteristics, goal, syllabus and contents of discrete mathematics course for pre-service teacher, followed by principles for teaching the subject.

• Journal of The Korean Society of Integrative Medicine
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• v.7 no.1
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• pp.65-74
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• 2019

Purpose : The purpose of this study was to determine the effects of 12 weeks of circuit training on inflammatory markers, blood lipids, and body composition of obese middle-aged women. Methods : Twenty-four obese women were randomly divided into three groups (circuit exercise training, CT; aerobic exercise training, AT; resistance exercise training, RT). All the subjects participated in the exercise program for 60 minutes, 3 times a week for 12 weeks. Results : Significant differences found in the participants pre-and post exercise training C-reactive protein (CRP), fibrinogen, and adiponectin levels. The CT participants experience an expected increase in their adiponectin levels. Significantly improved blood TC, LDL-C, HDL-C, and TG levels were found after 12 weeks of exercise. The AT and CT groups showed greater improvements in their HDL-C, LDL-C, and TG levels than the RT group. Significant differences were found in the participants pre-and post-exercise training body weight, body fat percentage, and body mass index (BMI). Conclusion : The CT participants body fat percentages decreased more than the RT group's percentages. In conclusion, obese women who completed 12 weeks of circuit exercise training (aerobics + resistance exercise) had significant improvements in their inflammatory markers, blood lipids, and body fat percentage.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.4
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• pp.145-152
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• 2020

MRC (Machine reading comprehension) is the AI NLP task that predict the answer for user's query by understanding of the relevant document and which can be used in automated consult services such as chatbots. Recently, the BERT (Pre-training of Deep Bidirectional Transformers for Language Understanding) model, which shows high performance in various fields of natural language processing, have two phases. First phase is Pre-training the big data of each domain. And second phase is fine-tuning the model for solving each NLP tasks as a prediction. In this paper, we have made the Patent MRC dataset and shown that how to build the patent consultation training data for MRC task. And we propose the method to improve the performance of the MRC task using the Pre-trained Patent-BERT model by the patent consultation corpus and the language processing algorithm suitable for the machine learning of the patent counseling data. As a result of experiment, we show that the performance of the method proposed in this paper is improved to answer the patent counseling query.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.251-273
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• 2022

Recently, research on applying text analysis to deep learning has steadily continued. In particular, researches have been actively conducted to understand the meaning of words and perform tasks such as summarization and sentiment classification through a pre-trained language model that learns large datasets. However, existing pre-trained language models show limitations in that they do not understand specific domains well. Therefore, in recent years, the flow of research has shifted toward creating a language model specialized for a particular domain. Domain-specific pre-trained language models allow the model to understand the knowledge of a particular domain better and reveal performance improvements on various tasks in the field. However, domain-specific further pre-training is expensive to acquire corpus data of the target domain. Furthermore, many cases have reported that performance improvement after further pre-training is insignificant in some domains. As such, it is difficult to decide to develop a domain-specific pre-trained language model, while it is not clear whether the performance will be improved dramatically. In this paper, we present a way to proactively check the expected performance improvement by further pre-training in a domain before actually performing further pre-training. Specifically, after selecting three domains, we measured the increase in classification accuracy through further pre-training in each domain. We also developed and presented new indicators to estimate the specificity of the domain based on the normalized frequency of the keywords used in each domain. Finally, we conducted classification using a pre-trained language model and a domain-specific pre-trained language model of three domains. As a result, we confirmed that the higher the domain specificity index, the higher the performance improvement through further pre-training.

• Journal of Korean Physical Therapy Science
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• v.16 no.2
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• pp.19-26
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• 2009

Background: The purpose of this study was to investigate effects of six-week biofeedback training for prevention of falling in elderly persons. Biofeedback training for using the TETRAX system. Methods: Thirty healthy elderly persons(men=17, women=13) who were 79 years of mean age participated in sensory regulation training. They were trained for thirty minutes a day, three times per week. We measured subjects sensory regulated function by TETRAX system, and analyzed mean difference of observed variables by paired t-test between the pre and post test. Results: The first experimental group were significantly difference between pre and post test. The second control group were not significantly between the pre and post test. The third there are significant between group. Conclusion: The results of this study reveal that biofeedback training exercise will improve sensory balance function, and further studies needs to identify which specific factors are related to fall in the elderly population, and it is expected this study may contribute in reducing fall and therapeutic exercise in falling.