• Journal of the Korea Society of Computer and Information
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• v.10 no.1 s.33
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• pp.45-52
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• 2005

We proposed the product recommendation algorithm mixed the temporal association rule and the exponential smoothing method. The temporal association rule added a temporal concept in a commercial association rule In this paper. we proposed a exponential smoothing temporal association rule that is giving higher weights to recent data than past data. Through simulation and case study in temporal data sets, we confirmed that it is more Precise than existing temporal association rules but consumes running time.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.741-746
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• 2004

As electronic commerce progresses, the temporal association rule is developed from partitioned data sets by time to offer personalized services for customer's interest. In this paper, we proposed a temporal association rule with exponential smoothing method that is giving higher weights to recent data than past data. Through simulation and case study, we confirmed that it is more precise than existing temporal association rules but consumes running time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.594-597
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• 2003

In this paper, we propose a new temporal error concealment method for recovery of video packet loss. Error concealment for each loss block is performed by temporal motion compensation and a smoothing operation of boundary pixels between the compensated block and its surrounding blocks. In the simulation results, performance improvement for the proposed technique is on the average 2 dB in comparison with the conventional technique.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1708-1713
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• 2003

In this paper, we propose a new temporal error concealment method for video packet loss. Error concealment for each loss block is performed by temporal motion compensation and a spatial smoothing operation of boundary pixels between the compensated block and its surrounding blocks. In the simulation results, performance improvement for the proposed technique is on the average 2㏈ in comparison with conventional techniques.

• The Journal of the Acoustical Society of Korea
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• v.10 no.3
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• pp.31-36
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• 1991

We propose an efficient pre-classification algorithm extracting candidate words to reduce the recognition time in a large-vocabulary recognition system and also propose the use of spectral and temporal smoothing of the observation probability to improve its classification performance. The proposed algorithm computes the coarse likelihood score for each word in a lexicon using the observation probabilities of speech spectra and duration information of recognition units. With the proposed approach we could reduce the computational amount by 74% with slight degradation of recognition accuracy in 1160-word recognition system based on the phoneme-level HMM. Also, we observed that the proposed coarse likelihood score computation algorithm is a good estimator of the likelihood score computed by the Viterbi algorithm.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.8
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• pp.26-33
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• 2017

Vehicle communication can facilitate efficient coordination among vehicles on the road and enable future vehicular applications such as vehicle safety enhancement, infotainment, or even autonomous driving. In the $3^{rd}$ Generation Partnership Project (3GPP), many studies focus on long term evolution (LTE)-based vehicle communication. Because vehicle speed is high enough to cause severe channel distortion in vehicle-to-vehicle (V2V) environments. We can utilize channel estimation methods to approach a reliable vehicle communication systems. Conventional channel estimation schemes can be categorized as least-squares (LS), decision-directed channel estimation (DDCE), spectral temporal averaging (STA), and smoothing methods. In this study, we propose a smart channel estimation scheme in LTE-based V2V environments. The channel estimation scheme, based on an LTE uplink system, uses a demodulation reference signal (DMRS) as the pilot symbol. Unlike conventional channel estimation schemes, we propose an adaptive smoothing channel estimation scheme (ASCE) using quadratic smoothing (QS) of the pilot symbols, which estimates a channel with greater accuracy and adaptively estimates channels in data symbols. In simulation results, the proposed ASCE scheme shows improved overall performance in terms of the normalized mean square error (NMSE) and bit error rate (BER) relative to conventional schemes.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.229-239
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• 2018

This paper introduces how to adopt the concept of temporal hierarchies to forecast time series data. Similarly as in hierarchical cross-sectional data, temporal hierarchies can be constructed for any time series data by means of non-overlapping temporal aggregation. Reconciliation forecasts with temporal hierarchies result in more accurate and robust forecasts when compared with the independent base and bottom-up forecasts. As an empirical example, we forecast traffic accident counts with temporal hierarchies and observe that reconciliation forecasts are superior to the base and bottom-up forecasts in terms of forecast accuracy.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.851-865
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• 2019

Discovering various features from one time series is complicated. In this paper, we introduce a multi aggregation prediction algorithm (MAPA) that uses the concepts of temporal aggregation and combining forecasts to find multiple patterns from one time series and increase forecasting accuracy. Temporal aggregation produces multiple time series and each series has separate properties. We use exponential smoothing methods in the next step to extract various features of time series components in order to forecast time series components for each series. In the final step, we blend predictions of the same kind of components and forecast the target series by the summation of blended predictions. As an empirical example, we forecast traffic accident counts using MAPA and observe that MAPA performance is superior to conventional methods.

• 한국전산유체공학회:학술대회논문집
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• 2001.10a
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• pp.11-19
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• 2001

An adaptive nonlinear artificial dissipation model is presented for performing aeroacoustic computations by the high-order and high-resolution numerical schemes based on the central finite differences. An effective formalism of it is devised by combining a selective background smoothing term and a well-established nonlinear shock-capturing term which is for the temporal accuracy as well as the numerical stability. A conservative form of the selective background smoothing term is presented to keep accurate phase speeds of the propagating nonlinear waves. The nonlinear shock-capturing term that has been modeled by the second-order derivative term is combined with it to improve the resolution of discontinuities and stabilize the strong nonlinear waves. It is shown that the improved artificial dissipation model with an adaptive control constant which is independent of problem types reproduces the correct profiles and speeds of nonlinear waves, suppresses numerical oscillations near discontinuity and avoids unnecessary damping on the smooth linear acoustic waves. The feasibility and performance of the adaptive nonlinear artificial dissipation model are investigated by the applications to actual computational aeroacoustics problems.