• Journal of Korean Physical Therapy Science
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• v.28 no.1
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• pp.33-45
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• 2021

Background: Children with cerebral palsy have difficulty acquiring motor skills through motor learning due to lack of motor planning of the central nervous system and musculoskeletal dysfunction. Motor learning is the acquisition or modification of movements with the aim of developing skilled movements and behaviors. Cerebral palsy improve motor function through motor learning, and effective motor learning mainly depends on practice parameters such as learning feedback. Therefore, we investigate the effect of motor learning in children with cerebral palsy and try to present the possibility of clinical application. Design: A systemic review. Methods: Research papers were published from Jan, 2010 to Dec, 2020 and were searched using PubMed and Medline. The search terms are 'task specific training' OR 'motor learning' OR 'feedback(Mesh term)' OR 'goal activity' AND 'cerebral palsy(Mesh term)'. A total of eight papers were analyzed in this study. The paper presented the quality level based on the research evidence, and also presented PEDro (Physiotherapy Evidence Database) scores to evaluate the quality of design studies in randomized clinical trials. Results: The results showed that motor learning coaching in children with cerebral palsy improved motor function in post and follow up tests. Also, self-control feedback of motor learning is more effective than external control feedback. 100% external control feedback of motor learning is effective in the acquisition phase and 50% external feedback of motor learning is effective in the retain phase. Conclusion: These results suggest that it will be an important data for establishing evidence on the effect of motor learning arbitration methods in children with cerebral palsy to develop clinical applicability and protocols.

• Journal of The Korean Society of Integrative Medicine
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• v.10 no.3
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• pp.37-52
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• 2022

Purpose : The purpose of this meta-analysis was to evaluate the effects of electrical stimulation on patients with non-specific low back pain. Methods : Domestic databases were gathered from studies that conducted clinical trials associated with electrical stimulation and its impact on pain of non-specific low back patients. A total of 681 studies were identified, with 12 studies satisfying the inclusion data. The studies consisted of patient, intervention, comparison, outcome, and study design (PICO-SD). The search outcomes were items associated with low back pain. Cochrane risk of bias 2 (RoB 2) was used to evaluate the quality of 12 randomized controlled trials. Effect sizes (Hedges's g) in this study were computed as the corrected standard mean difference (SMD). A random-effect model was used to analyze the effect size because of the high heterogeneity among the studies. Egger's regression and 'trim-and-fill' tests were carried out to analyze the publication bias. Cumulative meta-analysis and sensitivity analysis were conducted to analyze the effect according to the sample size and the consistency of the effect size. Results : The following factors had a large overall effect size (Hedges's g=1.28, 95 % CI=.20~2.36) involving electrical stimulation on non-specific low back pain. The subgroup analysis all showed a statistical difference in the types of study design, electrical stimulation, and assessment tool. No statistically significant difference was found in the meta-regression analysis. Publican bias was found in the data. Conclusion : The findings in this study indicate that electrical stimulation interventions have a positive effect on patients with non-specific low back pain. However, due to the low quality of studies and publication bias, the results of our study should be interpreted cautiously.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.139-147
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• 2009

BLAST (Basic Local Alignment Search Tool) is a best well-known tool in a bioinformatics area. BLAST quickly compares input sequences with annotated huge sequence databases and predicts their functions. It helps biologists to make it easy to annotate newly found sequences with reduced experimental time, scope, and cost. However, as the amount of sequences is increasing remarkably with the advance of sequencing machines, performance of BLAST has been a critical issue and tried to solve it with several alternatives. In this paper, we propose a new PC-Based Cluster system (E-Cluster), a new physical data design methodology (logical partitioning technique) and a query routing technique (intra-query routing). To verify our system, we measure response time, speedup, and efficiency for various sizes of sequences in NR (Non-Redundancy) database. Experimental result shows that proposed system has better speedup and efficiency (maximum 600%) than those o( conventional approaches such as SMF machines, clusters, and grids.

• Journal of Science of Art and Design
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• v.1
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• pp.95-123
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• 1999

The goal of this research is a visual and auditory tool development enabling designers to have the same emotional value with users in the process of user centered design. Through the research, we intend to show the aid measure for making cognitive gaps narrow between users and designer in the process of transforming and understanding the emotional needs as a verbal image. because In the business practice of design, most of tools and techniques for assessment and analysis of emotional needs are those used usually in the marketing fields. So the information generated and transformed from users to designers have a form of physical words. When the designer's understanding of the emotional needs is considered as a product mediated communication process, the morphologic and cognitive information gaps become obvious. This difference could be a false basis in designing with emotional user needs. So the alternative needs assessment sub-tools of visual and auditory information form was embodied mainly for designer's cognitive gaps and inter-cultural emotional needs assessment. As the method of embodiment, Firstly, adjectives related to emotion were classified in their cognitive dimension. Secondly, visual and auditory data were extracted, and then the relativity verified. Finally, the practicality and effectiveness were tested through the database generation. In view of the results so far achieved, 1. We could find being of the big information cognitive gaps in the verbal assessment of emotional needs between designers and users. 2. With the visual and auditory assessment tool, we could make the big cognitive gaps narrower than we expected. 3. Also, we could find the chance that the fidelity, recognition, and friendliness of design for emotional user needs would become better.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.345-354
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• 2005

Subsequence matching is one of the most important operations in the field of data mining. The existing subsequence matching algorithms use only one index, and their performance gets worse as the difference between the length of a query sequence and the site of windows, which are subsequences of a same length extracted from data sequences to construct the index, increases. In this paper, we propose a new subsequence matching method based on index interpolation to overcome such a problem. An index interpolation method constructs two or more indexes, and performs search ing by selecting the most appropriate index among them according to the given query sequence length. In this paper, we first examine the performance trend with the difference between the query sequence length and the window size through preliminary experiments, and formulate a search cost model that reflects the distribution of query sequence lengths in the view point of the physical database design. Next, we propose a new subsequence matching method based on the index interpolation to improve search performance. We also present an algorithm based on the search cost formula mentioned above to construct optimal indexes to get better search performance. Finally, we verify the superiority of the proposed method through a series of experiments using real and synthesized data sets.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.43-53
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• 2016

The purpose of this study is to examine the meaningfulness and the possibility of developing kinetic narrative educational contents based on English literature with convergent approaches. To accomplish the objective, this paper examines three areas of research such as kinetic education, English literature education, and total physical response-storytelling method. It introduces the following three stages of development procedure: 1) selecting and analyzing English literature, 2) designing a prototype including the story flow, the movement and the motion interaction design, and 3) constructing motion database using Laban movement analysis. Then, how to apply it to young learners is illustrated with 'the story of the three little pigs,' Finally, implication for the field of young learner English education and English literature is discussed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.14 no.1
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• pp.97-110
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• 1996

The purpose of this study is to evaluate the urban land used by the Urban Land Use Information System (ULIS) which can supply the micro-level land usc information for the understanding of micro-level urban spatial structure and district-level planning and managements(such as urban design, redevelopment planning and district-level transportation planning, etc.). The study evaluates the current situation of urban land use database and suggests the prototype of urban land use database using GIS. The planning and management of post-modern city which has characterized by diversity and the mixture of land use, need more detail and quantitative information about land use. Recent redevelopment and reconstruction of existing physical condition are increasing the density of activity. It raises urban problems such as the shortage of infrastructure and traffic congestion, etc. In this process we need to construct information system which monitors current land use situation.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1505-1514
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• 2004

Sequence matching in time-series databases is an operation that finds the data sequences whose changing patterns are similar to that of a query sequence. Typically, sequence matching hires a multi-dimensional index for its efficient processing. In order to alleviate the dimensionality curse problem of the multi-dimensional index in high-dimensional cases, the previous methods for sequence matching apply the Discrete Fourier Transform(DFT) to data sequences, and take only the first two or three DFT coefficients as organizing attributes of the multi-dimensional index. This paper first points out the problems in such simple methods taking the firs two or three coefficients, and proposes a novel solution to construct the optimal multi -dimensional index. The proposed method analyzes the characteristics of a target database, and identifies the organizing attributes having the best discrimination power based on the analysis. It also determines the optimal number of organizing attributes for efficient sequence matching by using a cost model. To show the effectiveness of the proposed method, we perform a series of experiments. The results show that the Proposed method outperforms the previous ones significantly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2021-2030
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• 2012

Premature ventricular contraction(PVC) is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Particularly, in the healthcare system that must continuously monitor patient's situation, it is necessary to process ECG (Electrocardiography) signal in realtime. In other words, the design of algorithm that exactly detects R wave using minimal computation and classifies PVC by analyzing the persons's physical condition and/or environment is needed. Thus, the patient adaptive pattern matching algorithm for the classification of PVC is presented in this paper. For this purpose, we detected R wave through the preprocessing method, adaptive threshold and window. Also, we applied pattern matching method to classify each patient's normal cardiac behavior through the Hash function. The performance of R wave detection and abnormal beat classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.33% in R wave detection and the rate of 0.32% in abnormal beat classification error.

• International Journal of Highway Engineering
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• v.8 no.3 s.29
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• pp.49-61
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• 2006

This study suggests long-life asphalt pavement method which can save maintenance cost by increasing the design and performance period of pavements. The high modulus asphalt binder developed and then various physical tests are performed. Laboratory performance tests and accelerated pavement test are conducted for the high modulus and conventional mixtures. The test results show that dynamic modulus values of high modulus mixtures are higher than those of the conventional mixtures, The high modulus mixtures yield better fatigue, rutting and moisture damage performance than conventional mixtures. Structural analysis is performed and a database is built up for long life asphalt pavement design. Pavement response model is developed through a multiple regression analysis program, SPSS using the database. A design software for the long life pavements is developed based on the pavement response model and laboratory and field performance tests results. In addition, optimum pavement sections and materials are suggested. The suggested AC thickness of long life asphalt pavement is 29cm. A Life cycle cost analysis(LCCA) is conducted to check the economical efficiency of the long life pavement section. The LCCA result shows that initial construction costs of long life and conventional pavements are almost equal, but long life pavement is more profitable in terms of the LCCA.