• The Journal of the Acoustical Society of Korea
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• v.22 no.3
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• pp.188-193
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• 2003

Regardless of the distribution of the adaptation data in the testing environment, model-based adaptation methods that have so far been reported in various literature incorporates the adaptation data undiscriminatingly in reducing the mismatch between the training and testing environments. When the amount of data is small and the parameter tying is extensive, adaptation based on outlier data can be detrimental to the performance of the recognizer. The distribution of the adaptation data plays a critical role on the adaptation performance. In order to maximally improve the recognition rate in the testing environment using only a small number of adaptation data, supervised weighted training is applied to the structural maximum a posterior (SMAP) algorithm. We evaluate the performance of the proposed weighted SMAP (WSMAP) and SMAP on TIDIGITS corpus. The proposed WSMAP has been found to perform better for a small amount of data. The general idea of incorporating the distribution of the adaptation data is applicable to other adaptation algorithms.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.1
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• pp.57-70
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• 2017

In this study, we evaluated daily root zone soil moisture dynamics and agricultural drought using a near-surface soil moisture data assimilation scheme with Soil Moisture Active & Passive (SMAP, $3km{\times}3km$) soil moisture footprints under different hydro-climate conditions. Satellite-based LANDSAT and MODIS image footprints were converted to spatially-distributed soil moisture estimates based on the regression model, and the converted soil moisture distributions were used for assessing uncertainties and applicability of SMAP data at fields. In order to overcome drawbacks of the discontinuity of SMAP data at the spatio-temporal scales, the data assimilation was applied to SMAP for estimating daily soil moisture dynamics at the spatial domain. Then, daily soil moisture values were used to estimate weekly agricultural drought based on the Soil Moisture Deficit Index (SMDI). The Yongdam-dam and Soyan river-dam watersheds were selected for validating our proposed approach. As a results, the MODIS/SMAP soil moisture values were relatively overestimated compared to those of the TDR-based measurements and LANDSAT data. When we applied the data assimilation scheme to SMAP, uncertainties were highly reduced compared to the TDR measurements. The estimated daily root zone soil moisture dynamics and agricultural drought from SMAP showed the variability at the sptio-temporal scales indicating that soil moisture values are influenced by not only the precipitation, but also the land surface characteristics. These findings can be useful for establishing efficient water management plans in hydrology and agricultural drought.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.520-528
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• 2003

This paper proposes a method of implementing synthetic stereo and an acoustic echo cancellation algorithm for multiple participant conference system. Synthetic stereo is generated by HRTF and two loudspeakers. A robust adaptive algorithm for synthetic stereo echo cancellation is proposed to reduce the weight misalignment due to near-end speech signals and ambient noises. The proposed adaptive algorithm is modified version of SMAP algorithm and the coefficients of adaptive filter is updated with cross correlation of input and estimation error signal normalized with sum of the autocorrelation of input signal and the power of the estimation error signal multiplied with projection order. This is more robust to projection order and ambient noise than conventional SMAP. Computer simulation show that the proposed algorithm effectively attenuates synthetic stereo acoustic echo.

• Proceedings of the Korean Geotechical Society Conference
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• 1991.10a
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• pp.271-288
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• 1991

SMAP-S2 is an advanced too-dimensional , static finite element computer program developed for the geometric and material nonlinear structure-medium interaction analysis. The program has specific applications for modeling geomechanical problems associated with multi-staged excavation or embankment. Theoretical formulations and computational algorithms are presented along with the description of elasto-plastic material models. Nonlinear features of the code are verified by comparing with known solutions or experimental test results. Capabilities of per- and post-processing programs are discussed.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.05b
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• pp.423-426
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• 2003

Adaptive algorithm used in Acoustic Echo Canceller (AEC) needs fast convergence algorithm when reference signal is colored speech signal. Set-Membership Affine Projection (SMAP) algorithm is derived from the constraint, which is the minimum value adaptive filter coefficient error. In this paper, we test the characteristic about noise of the SMAP algorithm and proposed modified version of SMAP algorithm fur using at AEC. As the projection order increase, the convergence characteristic of the SMAP algorithm is improved where no noise space. But if the noise uncorrelated with input signal exists, the AEC shows bad performance. In this paper, we propose normalized version of adaptive constants using estimated error signal for robust to noise and show the good performance through AEC simulation.

• Physical Therapy Korea
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• v.20 no.2
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• pp.52-59
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• 2013

The purpose of this study was to determine the reliability and validity of the postural balance program which uses the movement accelerating field principles of posture balance training and evaluation equipment and smartphone movement accelerometer program (SMAP) in healthy young adults. A total of 34 people were appointed as the subject among the healthy young adults. By using Biodex stability system (BSS) and SMAP on the subject, the posture balance capability was evaluated. For the test-retest reliability, SMAP showed the intra-class correlation (ICC: .62~.91) and standard error measurement (SEM: .01~.08). BSS showed the moderate to high reliability of ICC (.88~.93) and SEM (.02~.20). In the reliability of inter-rater, ICC (.59~.73) as to SMAP, showed the reliability of moderate in eyes open stability all (EOSA), eyes open stability anterior posterior (EOSAP), eyes open stability medial lateral (EOSML) and eyes open dinamic all (EODA), eyes open danamic anterior posterior (EODAP), and eyes open danamic medial lateral (EODML). However, ICC showed reliability which was as low as .59 less than in other movements. In addition, BSS showed the reliability of high as ICC (.70~.75). It showed reliability which was as low as ICC (.59 less than) in other movements. In correlation to the balance by attitudes between SMAP and BSS, EOSML (r=.62), EODA (r=.75), EODML (r=.72), ECDAP (r=.64), and ECDML (r=.69) shown differ significantly (p<.05). However, the correlation noted in other movements did not differ significantly. Therefore, SMAP and BSS can be usefully used in the posture balance assessment of the static and dynamic condition with eyes opened and closed.

• PNF and Movement
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• v.13 no.1
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• pp.39-46
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• 2015

Purpose: The accelerometer is a tool for evaluating walking by the displacement of the center of mass (COM) in the body. Recently, smartphones have added an accelerometer app, and it can be used to evaluate outcomemanures in rehabilitation. The purpose of this study was to investigate the COM in the bodies of normal persons and stroke patients using this smartphone application while walking. Methods: Twenty normal persons and twenty-two stroke patients were recruited and had their COM measured using G-walk and the smartphone application, SMAP, during 10 m walking. Subjects repeated the 10 m of walking 3 times, and we used the SMAP, Accelerometer Monitor ver. 1.5.0, to evaluate COM during the walk. To measure the displacement of COM, we used the difference in value between the maximal angle and the minimum anterior-posterior (AP), mediolateral (ML), and rotational angles during the walk. Results: For the normal persons, there was significant correlation between the AP and AP of SMAP, and was also a significant correlation between rotational angle and the ML of SMAP. In the stroke patients, there was significant correlation between AP and ML, and the rotational angle of SMAP. Conclusion: Our research results suggest that if the SMAP system is reinforced in the case of patients who have a greater displacement of COM, it may be used as an evaluation tool during walking.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1185-1193
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• 2023

The increasing interest in soil moisture data from satellite imagery for applications in hydrology, meteorology, and agriculture has led to the development of methods to produce variable-resolution soil moisture maps. Research on accurate soil moisture estimation using satellite imagery is essential for remote sensing applications. The purpose of this study is to generate a soil moisture estimation map for a test area using KOMPSAT-3/3A and KOMPSAT-5 SAR imagery and to quantitatively compare the results with soil moisture data from the Soil Moisture Active Passive (SMAP) mission provided by NASA, with a focus on accuracy validation. In addition, the Korean Environmental Geographic Information Service (EGIS) land cover map was used to determine soil moisture, especially in agricultural and forested regions. The selected test area for this study is the western part of Jeju, South Korea, where input data were available for the soil moisture estimation algorithm based on the Water Cloud Model (WCM). Synthetic Aperture Radar (SAR) imagery from KOMPSAT-5 HV and Sentinel-1 VV were used for soil moisture estimation, while vegetation indices were calculated from the surface reflectance of KOMPSAT-3 imagery. Comparison of the derived soil moisture results with SMAP (L-3) and SMAP (L-4) data by differencing showed a mean difference of 4.13±3.60 p% and 14.24±2.10 p%, respectively, indicating a level of agreement. This research suggests the potential for producing highly accurate and precise soil moisture maps using future South Korean satellite imagery and publicly available data sources, as demonstrated in this study.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.152-152
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• 2018

Soil moisture is a important factor in hydrologic analysis. So, if we have spatially distributed soil moisture data, it can help to study much research in a various field. Recently, there are a lot of satellite derived soil moisture data, and it can be served through web freely. Especially, NASA (National Aeronautics and Space Administration) launched the Soil Moisture Aperture Passive (SMAP) satellite for mapping global soil moisture on 31 January 2015. SMAP data have many advantages for study, for example, SMAP data has higher spatial resolution than other satellited derived data. However, becuase many satellited derived soil moisture data have a limitation to data accuracy, if we have ancillary materials for improving data accuracy, it can be used. So, in this study, after applying the alogorithm, which is data assimilation methods, applicability of satellite derived soil moisture data was analyzed. Among the various data assimilation methods, in this study, Model Output Statistics (MOS) technique was used for improving satellite derived soil moisture data. Model Output Statistics (MOS) is a type of statistical post-processing, a class of techniques used to improve numerical weather models' ability to forecast by relating model outputs to observational or additional model data.