• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.77-85
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• 2020

The purpose of this study is to explore the changing trajectory of using educational media through longitudinal data analysis. We categorize the feature of using educational media as usage for learning, usage for information, and usage for the game. We explore the longitudinal changing patterns of usage for learning, usage for information, and usage for the game by LGM(Longitudinal Growth Modeling). We also find the gender difference between these longitudinal changing trajectories. We used 3,499 samples of KYPS middle school second-grade panel data. We found these results: (a) Both usage for learning and information are statically significant variability in initial level and rate of change. Both of the changing trajectories have increased. (b) Girls have a higher rate of the change both in the usage of learning and information than boys over time. (c) There is a statistically significant individual variability in initial levels and rate of change in the usage of the game over time. (d) Boys have a higher rate of initial value than girls in the usage of games, but there is no significant difference in the rate of changing trajectories.

• Journal of the Korean Recycled Construction Resources Institute
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• v.5 no.1
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• pp.1-7
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• 2017

Concrete behavior in early-age is changing due to hydration reaction with time, and a resistance to chloride attack and strength development are different characterized. In the present work, changing strength and resistance to chloride attack are evaluated with ages from 28 days to 6 months. For the purpose, strength, diffusion coefficient, and passed charge are evaluated for normal concrete with 3 different mix proportions considering 28-day and 6-month curing conditions. With increasing concrete age, the changing ratio of strength falls on the level of 135.3~138.3%, while diffusion coefficient and passed charge shows 41.8%~51.1% and 53.6%~70.0%, respectively. The results of chloride diffusion coefficient and passed charge show relatively similar changing ratios since they are much dependent on the chloride migration velocity in electrical field. The changing ratios in chloride behaviors are evaluated to be much larger than those in compressive strength since the ion transport mechanism is proportional to not porosity but square of porosity.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.457-468
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• 1997

The present paper deals with an economic order quan-tity model for items deteriorating at some constant rate with demand changing at a known and at a random point of time in the fixed pro-duction cycle.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.467-470
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• 2003

When user wants to find objects which have the nearest position from him, we use the nearest neighbor (NN) query. The GIS applications, such as navigation system and traffic control system, require processing of NN query for moving objects (MOs). MOs have trajectory with changing their position over time. Therefore, we should be able to find NN object continuously changing over the whole query time when process NN query for MOs, as well as moving nearby on trajectory of query. However, none of previous works consider trajectory information between objects. Therefore, we propose a method of continuous NN query for trajectory of MOs. We call this CTNN (continuous trajectory NN) technique. It ran find constantly valid NN object on the whole query time by considering of trajectory information.

• Korean Journal of Agricultural Science
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• v.41 no.2
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• pp.119-124
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• 2014

Feeding behaviors of the sweet potato whitefly, Bemisia tabaci, and changing of their feeding behaviors were recorded and analyzed with an Electrical Penetration Graph (EPG) analysis against cyantraniliprole. The characteristic patterns of feeding behaviors investigated were as follows; NP (non probing), pathway phase waveform, waveform of feeding xylem. In results, B. tabaci did not almost feeding the phloem. And It was not appeared potential drop during recording time. It was predominantly indicated pathway activity waveform and waveform of xylem feeding. After treatment of cyantraniliprole with recommended concentrations to tomato plants, EPG waveforms were recorded during 3 hours. Cyantraniliprole treatment showed longer time to first feeding xylem than untreated (P=0.043). It was showed shorter duration of first feeding xylem than untreated (P=0.017). And it was showed longer NP (non-probing) time than untreated. Consequently, It was supposed that cyantraniliprole was effect of anti-feeding or avoidance to B. tabaci.

• Proceedings of the Materials Research Society of Korea Conference
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• 2010.05a
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• pp.23.2-23.2
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• 2010

Researches on the drying of particle/polymer suspensions receive attentions in technical applications such as manufacturing display and batteries. In this study, the effect of polymers on drying behavior of silica/poly(vinyl alcohol) suspension was investigated in terms of suspension stability and stress development during drying. The effect of polymer adsorption was studied by changing pH. More strongly flocculated suspension with lower pH became more dispersed and close-packed film after drying. Evaluation of potential energy allows us to suggest that the adsorbed polymers which bridge the particles introduce steric repulsion and lead flocculated suspension to dispersed film. When the effect of adsorption kinetics was studied by changing the mixing time, the adsorption amount, characteristic stress and dried film density showed a similar behavior in the form of with a single characteristic time. It implies that the drying process can be determined by simple characteristic equation with a single time constant.

• International Journal of Aeronautical and Space Sciences
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• v.2 no.1
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• pp.103-109
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• 2001

Productivity enhancement program of wind tunnel testing has begun at Korea Aerospace Research Institute Low Speed Wind Tunnel (KARI LSWT). A previous test record of a canard airplane model was adopted to examine the current status of wind tunnel testing efficiency. The time consumed to perform testing activities from the model preparation to data collection was broken down and the results were compared with those of the recent Boeing low speed test result. The efforts to improve the wind tunnel productivity consisted of the installation of mini crane underneath of test section, fabricating lift device for image fairings, model configuration changing rigs and the modifications of external balance system. Time reductions for changing strut interface platform and installation of image fairings. These effects showed more than 70% improvement over the previous test time. Integration of the new and modified systems will improve productivity of wind tunnel testing in KARI LSWT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4664-4681
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• 2020

Modulation recognition (MR) plays a key role in cognitive radar, cognitive radio, and some other civilian and military fields. While existing methods can identify the signal modulation type by extracting the signal characteristics, the quality of feature extraction has a serious impact on the recognition results. In this paper, an end-to-end MR method based on long short-term memory (LSTM) and the gated recurrent unit (GRU) is put forward, which can directly predict the modulation type from a sampled signal. Additionally, the sliding window method is applied to fast-changing mixed-modulation signals for which the signal modulation type changes over time. The recognition accuracy on training datasets in different SNR ranges and the proportion of each modulation method in misclassified samples are analyzed, and it is found to be reasonable to select the evenly-distributed and full range of SNR data as the training data. With the improvement of the SNR, the recognition accuracy increases rapidly. When the length of the training dataset increases, the neural network recognition effect is better. The loss function value of the neural network decreases with the increase of the training dataset length, and then tends to be stable. Moreover, when the fast-changing period is less than 20ms, the error rate is as high as 50%. As the fast-changing period is increased to 30ms, the error rates of the GRU and LSTM neural networks are less than 5%.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.1-7
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• 2018

Purpose: Maintaining appropriate operational availability (Ao) is a key element of combat victory, but estimates vary according to estimation methods. The purpose of this study is to improve the accuracy of estimating operational availability by tracing the changes of the weapon system's failure rate, repair rate, and the level of logistic support. Methods: In order to track the change in the operating availability, the MDT (mean down time) is modeled by adding the repair time and the ALDT (administration and logistic delay time) to the service time. Results: Using the field data of the weapon system A operated by the ROKAF, the failure rate follows a non-homogeneous Poisson process that changes with time, and it is modeled considering the changing repair rate and the logistic support time. Conclusion: The accuracy of the analytical results was verified by comparing the actual operating data with the estimated availability. The results of this study can be used to track and evaluate the availability in a realistic situation where the failure rate and maintenance rate continuously change in operating environment.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.149-163
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• 2023

Affected by external factors, errors in time series data collected by sensors are common. Using the traditional method of constraining the speed change rate to clean the errors can get good performance. However, they are only limited to the data of stable changing speed because of fixed constraint rules. Actually, data with uneven changing speed is common in practice. To solve this problem, an online cleaning algorithm for time series data based on dynamic speed change rate constraints is proposed in this paper. Since time series data usually changes periodically, we use the extreme learning machine to learn the law of speed changes from past data and predict the speed ranges that change over time to detect the data. In order to realize online data repair, a dual-window mechanism is proposed to transform the global optimal into the local optimal, and the traditional minimum change principle and median theorem are applied in the selection of the repair strategy. Aiming at the problem that the repair method based on the minimum change principle cannot correct consecutive abnormal points, through quantitative analysis, it is believed that the repair strategy should be the boundary of the repair candidate set. The experimental results obtained on the dataset show that the method proposed in this paper can get a better repair effect.