• Korean Journal of Applied Biomechanics
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• v.26 no.4
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• pp.353-360
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• 2016

Objective: The aim of this study was to investigate the relationship between aiming patterns and scores in archery shooting. Method: Four (N = 4) elementary-level archers from middle school participated in this study. Aiming pattern was defined by averaged acceleration data measured from accelerometers attached on the body during the aiming phase in archery shooting. Stepwise multiple regression analysis was used to test whether a model incorporating aiming patterns from all nine accelerometers could predict the scores. In order to extract period of interest (POI) data from raw data, a Dynamic Time Warping (DTW)-based extraction method was presented. Results: Regression models for all four subjects are conducted with different significance levels and variables. The significance levels of the regression models are 0.12%, 1.61%, 0.55%, and 0.4% respectively; the $R^2$ of the regression models is 64.04%, 27.93%, 72.02%, and 45.62% respectively; and the maximum significance levels of parameters in the regression models are 1.26%, 4.58%, 5.1%, and 4.98% respectively. Conclusion: Our results indicated that the relationship between aiming patterns and scores was described by a regression model. Analysis of the significance levels, variables, and parameters of the regression model showed that our approach - regression analysis with DTW - is an effective way to raise scores in archery shooting.

• Journal of Internet Computing and Services
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• v.20 no.1
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• pp.39-46
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• 2019

This paper investigates the importance of various environmental factors that have a strong influence on strawberry yields grown in greenhouse using the pattern recognition methods. The environmental factors influencing the production of strawberries were six factors such as average inside temperature, average inside humidity, average $CO_2$ level, average soil temperature, cumulative solar radiation, and average illumination. The results of analyzing the observed data using Dynamic Time Warping (DTW) showed that the most significant factor influencing the strawberry production was average soil temperature, average inside humidity, and cumulative solar radiation. Second, the results of analyzing the observed data using Multidimensional Scaling (MDS) showed that the most influential factors on the strawberry yields, such as average $CO_2$ level, average inside humidity, and average illumination were differently given for each farms. However, these results are based on the distance in 3D space and can be deduced from the fact that there is not a large difference between these distances. Therefore, in order to increase the harvest of strawberries cultivated in the farms, it is necessary to manage the environmental factors such as thoroughly controlling the humidity and maintaining the concentration of $CO_2$ constantly by ventilation of the greenhouse.

• Journal of applied mathematics & informatics
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• v.41 no.6
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• pp.1257-1274
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• 2023

Rotating machines heavily rely on an intricate network of interconnected sub-components, with bearing failures accounting for a substantial proportion (40% to 90%) of all such failures. To address this issue, intelligent algorithms have been developed to evaluate vibrational signals and accurately detect faults, thereby reducing the reliance on expert knowledge and lowering maintenance costs. Within the field of machine learning, Artificial Immune Systems (AIS) have exhibited notable potential, with applications ranging from malware detection in computer systems to fault detection in bearings, which is the primary focus of this study. In pursuit of this objective, we propose a novel procedure for detecting novel instances of anomalies in varying operating conditions, utilizing only the signals derived from the healthy state of the analyzed machine. Our approach incorporates AIS augmented by Dynamic Time Warping (DTW). The experimental outcomes demonstrate that the AIS-DTW method yields a considerable improvement in anomaly detection rates (up to 53.83%) compared to the conventional AIS. In summary, our findings indicate that our method represents a significant advancement in enhancing the resilience of AIS-based novelty detection, thereby bolstering the reliability of rotating machines and reducing the need for expertise in bearing fault detection.

• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.53-60
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• 2018

This paper describes the experiments of gaze tracking utilizing a low-cost electrooculogram measuring device. The goal of the experiments is to verify whether the low-cost device can be used for a complicated human-computer interaction tool, such as the eye-writing. Two experiments are conducted for this goal: a simple gaze tracking of four directional eye-movements, and eye-writing-which is to draw letters or shapes in a virtual space. Eye-written alphabets were obtained by two PSL-iEOGs and an Arduino Uno; they were classified by dynamic positional warping after preprocessed by a wavelet function. The results show that the expected recognition accuracy of the four-directional recognition is close to 90% when noises are controlled, and the similar median accuracy (90.00%) was achieved for the eye-writing when the number of writing patterns are limited to five. In future works, additional algorithms for stabilizing the signal need to be developed.

• Journal of Broadcast Engineering
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• v.1 no.2
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• pp.85-95
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• 1996

The purpose of this paper Is to propose a dubbed signal time-synchroniztion technique based on the SOLA(Synchronized Over-Lap and Add) method which has been widely used to modify the time scale of speech signal. In broadcasting audio recording environments, the high degree of background noise requires dubbing process. Since the time difference between the original and the dubbed signal ranges about 200mili seconds, process is required to make the dubbed signal synchronize to the corresponding image. The proposed method finds he starting point of the dubbing signal using the short-time energy of the two signals. Thereafter, LPC cepstrum analysis and DTW(Dynamic Time Warping) process are applied to synchronize phoneme positions of the two signals. After determining the matched point by the minimum mean square error between orignal and dubbed LPC cepstrums, the SOLA method is applied to the dubbed signal, to maintain the consistency of the corresponding phase. Effectiveness of proposed method is verified by comparing the waveforms and the spectrograms of the original and the time synchronized dubbing signal.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.363-370
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• 2023

Due to the spread of COVID-19, the use of public transportation such as urban railroads has changed significantly since the beginning of 2020. Therefore, in this study, daily time series data for each urban railway station were collected for three years before COVID-19 and after the spread of COVID-19, and the similarity of time series analysis was evaluated through DTW (Dynamic Time Warping) distance method to derive regression centers for each cluster, and the effect of various external events such as COVID-19 on changes in the number of users was diagnosed as a time series impact detection function. In addition, the characteristics of use by cluster of urban railway stations were analyzed, and the change in passenger volume due to external shocks was identified. The purpose was to review measures for the maintenance and recovery of usage in the event of re-proliferation of COVID-19.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.599-605
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• 2017

Accurate cloud discrimination in satellite images strongly affects accuracy of remotely sensed parameter produced using it. Especially, cloud contaminated pixel over ocean is one of the major error factors such as Sea Surface Temperature (SST), ocean color, and chlorophyll-a retrievals,so accurate cloud detection is essential process and it can lead to understand ocean circulation. However, static threshold method using real-time algorithm such as Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Himawari Imager (AHI) can't fully explained reflectance variability over ocean as a function of relative positions between the sun - sea surface - satellite. In this paper, we assembled a reflectance spectral library as a function of Solar Zenith Angle (SZA) and Viewing Zenith Angle (VZA) from ocean surface reflectance with clear sky condition of Advanced Himawari Imager (AHI) identified by NOAA's cloud products and spectral library is used for applying the Dynamic Time Warping (DTW) to detect cloud pixels. We compared qualitatively between AHI cloud property and our results and it showed that AHI cloud property had general tendency toward overestimation and wrongly detected clear as unknown at high SZA. We validated by visual inspection with coincident imagery and it is generally appropriate.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.6
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• pp.583-592
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• 2010

Equations of motion of thin-walled composite H-type cross-section beams exposed to concentrated harmonic and non-harmonic time-dependent external excitations, incorporating a number of nonclassical effects of transverse shear, primary and secondary warping, and anisotropy of constituent materials are derived. The forced vibration response characteristics of a composite H-type cross-section beam exhibiting the circumferentially asymmetric stiffness(CAS) configuration are exploited in connection with the structural bending-torsion coupling resulting from directional properties of fiber reinforced composite materials.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.1129-1135
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• 1999

isolated word recognition using the Dynamic Time warping algorithm has shown good recognition rate on speaker dependent environment. But, practically, since the searching time of the dynamic Time Warping algorithm is rapidly increased as searching data is increased. it is hard to implement. In the context-dependent-short-query system such as educational children's workbook on the Web, the number of responses to the specific questions is limited. Therefore, the searching space for the answers can be reduced depending on the questions. In this paper, low cost implementation method using DTW for the Web has been proposed. To cover the weakness of DTW, the searching space is reduced by the context. the searching space, depends on the specific questions, is chosen from interest searchable candidates. In the real implementation, the proposed method show better performance of both time and recognition rate.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.2
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• pp.129-136
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• 2020

Recognizing finger movements have been used as a intuitive way of human-computer interaction. In this study, we implement an wearable device for finger motion recognition and evaluate the accuracy of several ML (Machine learning) techniques. Not only HMM (Hidden markov model) and DTW (Dynamic time warping) techniques that have been traditionally used as time series data analysis, but also NN (Neural network) technique are applied to compare and analyze the accuracy of each technique. In order to minimize the computational requirement, we also apply the pre-processing to each ML techniques. Our extensive evaluations demonstrate that the NN-based gesture recognition system achieves 99.1% recognition accuracy while the HMM and DTW achieve 96.6% and 95.9% recognition accuracy, respectively.