• Annals of Geriatric Medicine and Research
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• v.21 no.1
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• pp.17-23
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• 2017

Background: In at-risk older adults, gait speed is an important factor associated with quality of life and falling risk. In this study, we assessed whether therapeutic exercise could improve gait speed. Methods: We conducted a meta-analysis to evaluate the 'best' therapeutic exercise method by analyzing each exercise in terms of intensity, type, and several gait speed indices. For the analysis, we gathered 122 papers through a database search and selected 9 (n=627) that were appropriate for the meta-analysis. Results: In 8 of the 9 included papers, gait speed improved with therapeutic exercise. Usual gait speed (n=246) improved more than maximal gait speed (n=574). A resistance program was more effective than a nonresistance program for improving maximal, but not usual, gait speed. We also found that the effects of therapeutic exercise were greater in noncommunity than in community-dwelling elderly people. Conclusion: In conclusion, therapeutic exercise was effective in improving gait speed.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2019.11a
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• pp.205-206
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• 2019

National Competency Standard(NCS) is a national organization that organizes the knowledge, skills, and quality required to perform duties at industrial sites by industry sector and level. As NCS was developed and adopted as part of the government's implementation of capability-oriented society, the construction industry is also fully applying NCS to the curriculum and training. This study investigated and analyzed the problems of NCS development in construction work field through prior research analysis and experts interview and derived problems such as discrepancies in classification system, lack of connectivity with curriculum, and lack of effectiveness in revising NCS in construction work field. Further research is thought to be necessary for the establishment of the development system reflecting the construction characteristics in the future and for the presentation of practical improvement directions.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.81-86
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• 2018

Software defect severity is very important in projects with limited historical data or new projects. But general software defect prediction is very difficult to collect the label information of the training set and cross-project defect prediction must have a lot of data. In this paper, an unclassified data set with defect severity is clustered according to the distribution ratio. And defect severity-based prediction model is proposed by way of labeling. Proposed model is applied CLAMI in JM1, PC4 with the least ambiguity of defect severity-based NASA dataset. And it is evaluated the value of ACC compared to original data. In this study experiment result, proposed model is improved JM1 0.15 (15%), PC4 0.12(12%) than existing defect severity-based prediction models.

• Journal of Fisheries and Marine Sciences Education
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• v.23 no.4
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• pp.673-683
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• 2011

The purpose of this study was to analyze the validity of teacher evaluation policy for professional development and to suggest the ways to improve the policy in school. The teacher evaluation policy for professional development is designed to improve teacher professionalism and quality of school education. For this purpose, A survey was conducted and 361 elementary and middle school teachers participated in Busan. Collected data were analyzed using SPSS WIN 12.0. The conclusions of this study are as follows: First, although teachers are highly interested in the teacher evaluation policy, they have negative attitudes for practicing the new policy. Second, assessors must be composed of reliable, competent experts because teacher evaluation has a great influence on teaching activities. The assessors should be composed of those who have the specialization and reliability on the basis. Also the assessors must be trained to enhance the fairness, objectivity and reliability by rigid discipline. Finally, teacher evaluation policy should be closely linked to increasing teacher's expertise such as training opportunities, teacher consultants, and senior teacher systems and should be widely utilized for the evaluation to be effective.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1403-1413
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• 2021

In this paper, we investigate automated data validation techniques for artificial intelligence training, and also disclose open-source frameworks, such as Google's TensorFlow Data Validation (TFDV), that support automated data validation in the AI model development process. We also introduce an experimental study using public data sets to demonstrate the effectiveness of the open-source data validation framework. In particular, we presents experimental results of the data validation functions for schema testing and discuss the limitations of the current open-source frameworks for semantic data. Last, we introduce the latest studies for the semantic data validation using machine learning techniques.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1319-1325
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• 2021

It is important to remove fog for accurate object recognition and detection during preprocessing because images taken in foggy adverse weather suffer from poor quality of images due to scattering and absorption of light, resulting in poor performance of various vision-based applications. This paper proposes an end-to-end deep learning-based single image de-fogging method using U-Net architecture. The loss function used in the algorithm is a loss function based on Mahalanobis distance with fog features, which solves the problem of domain shifts, and demonstrates superior performance by comparing qualitative and quantitative numerical evaluations with conventional methods. We also design it to generate fog through the VGG19 loss function and use it as the next training dataset.

• Journal of Yeungnam Medical Science
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• v.38 no.4
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• pp.282-288
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• 2021

Medication alone is not sufficient to treat insomnia. In addition, the side effects of sleep medications themselves cannot be ignored during treatment. Insomnia begins with poor sleep quality and discomfort, but as it continues, patients fall into a vicious circle of insomnia with negative thoughts and dysfunctional and distorted perceptions related to sleep. Mindfulness-based intervention for insomnia corrects these sequential cognitive and behavioral processes. The mindfulness technique basically recognizes all the thoughts, feelings, and experiences that occur to us as they are, nonjudgmentally, and then trains them to return to the senses of our body. In this way, while noticing all the processes of the sequential vicious cycle and training them to return to our bodies (e.g., breathing), mindfulness determines whether we are really sleepy or just fatigued. This mindfulness-based intervention can be a useful nonpharmaceutical intervention for insomnia, and its stability and efficacy has been proven by many studies.

• ETRI Journal
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• v.43 no.2
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• pp.288-298
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• 2021

Abstractive text summarization is a process of making a summary of a given text by paraphrasing the facts of the text while keeping the meaning intact. The manmade summary generation process is laborious and time-consuming. We present here a summary generation model that is based on multilayered attentional peephole convolutional long short-term memory (MAPCoL; LSTM) in order to extract abstractive summaries of large text in an automated manner. We added the concept of attention in a peephole convolutional LSTM to improve the overall quality of a summary by giving weights to important parts of the source text during training. We evaluated the performance with regard to semantic coherence of our MAPCoL model over a popular dataset named CNN/Daily Mail, and found that MAPCoL outperformed other traditional LSTM-based models. We found improvements in the performance of MAPCoL in different internal settings when compared to state-of-the-art models of abstractive text summarization.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.165-171
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• 2021

The current study investigated cyber learners' use and perceptions of online machine translation (MT) tools. The results show that learners use several MT tools frequently and extensively for various second language learning (L2) purposes according to their needs. The learners' overall perceptions of using MT for English learning were generally positive. The learners reported several advantages of machine translation: ease of use, helpful feedback, effective revision, and facilitation of self-directed learning. At the same time, a considerable number of learners were aware of MT's drawbacks, such as awkward sentences, inaccurate grammar, and inappropriate words, and thus held a negative or skeptical view on the quality and accuracy of MT. These findings have important pedagogical implications for using MT in the context of a cyber university. For successful integration of MT in English classes, teachers need to provide appropriate guidelines and training that will help learners use MT effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.8
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• pp.4270-4284
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• 2019

This study presents a reference model (RM) and the architecture of a cognitive health advisor (CHA) that integrates information with ambient intelligence. By controlling the information using the CHA platform, the reference model can provide various ambient intelligent solutions to a user. Herein, a novel approach to a CHA RM based on evolutional cyber-physical systems is proposed. The objective of the CHA RM is to improve personal health by managing data integration from many devices as well as conduct a new feedback cycle, which includes training and consulting to improve quality of life. The RM can provide an overview of the basis for implementing concrete software architectures. The proposed RM provides a standardized clarification for developers and service designers in the design and implementation process. The CHA RM provides a new approach to developing a digital healthcare model that includes integrated systems, subsystems, and components. New features for chatbots and feedback functions set the position of the conversational interface system to improve human health by integrating information, analytics, and decisions and feedback as an advisor on the CHA platform.