• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.221-226
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• 2024

In information retrieval, queries come in various types, ranging from abstract queries to those containing specific keywords, making it a challenging task to accurately produce results according to user demands. Additionally, search systems must handle queries encompassing various elements such as typos, multilingualism, and codes. Reranking is performed through training suitable documents for queries using DeBERTa, a deep learning model that has shown high performance in recent research. To evaluate the effectiveness of the proposed method, experiments were conducted using the test collection of the Product Search Track at the TREC 2023 international information retrieval evaluation competition. In the comparison of NDCG performance measurements regarding the experimental results, the proposed method showed a 10.48% improvement over BM25, a basic information retrieval model, in terms of search through query error handling, provisional relevance feedback-based product title-based query expansion, and reranking according to query types, achieving a score of 0.7810.

• Journal of the Korean Society of Physical Medicine
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• v.19 no.3
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• pp.55-63
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• 2024

PURPOSE: This study examined the test-retest reliability and clinical utility of the Modified Trunk Impairment Scale (mTIS), Trunk Control Test (TCT), and Postural Assessment Scale for Stroke - Trunk Control (PASS-TC) in patients with chronic stroke. METHODS: Thirty-eight stroke patients were reassessed using the mTIS, TCT, and PASS-TC with a seven-day interval between assessments. The test-retest reliability was evaluated using the intraclass correlation coefficient (ICC_2,1), the standard error of measurement (SEM), the minimal detectable change (MDC), and MDC%, as well as Bland-Altman analysis. The relationship between the mTIS, TCT, PASS-TC scores, and the Barthel Index (BI) was also investigated. RESULTS: The test-retest reliability for the mTIS, TCT, and PASS-TC was high, with ICC values ranging from .91 to .94 (95% confidence interval: .83-.97). The MDCs for the mTIS and TCT were 2.35 and 13.9, respectively, while the MDC for the P ASS-TC was 2.54, all below 20% of the maximum possible score, indicating reliable measurement. The optimal mTIS cut-off score for distinguishing between mild (75-95 points) and severe (50-74 points) dependence on the BI was ≥ 9.5, with an accuracy of 79%. Patients with an mTIS score ≥ 9.5 (out of 15) showed an 18-fold higher likelihood of achieving a mild level of functional independence than those with a score < 9.5. CONCLUSION: The mTIS, TCT, and PASS-TC showed high test-retest reliability and no systematic errors in chronic stroke patients. The MDC values were reliable, indicating meaningful change. Among these, the mTIS is a sensitive and a useful tool for predicting functional independence in clinical practice and is straightforward to apply.

• Journal of Korean Society for Atmospheric Environment
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• v.27 no.2
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• pp.201-208
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• 2011

Recently, a real-time, pocket-sized aethalometer (microAeth$^{(R)}$ model AE51) has been developed by Magee Scientific Inc. for measuring the concentration of black carbon in the atmosphere. In this study, two aethalometers, models AE-16 and AE-51, which measure the optical absorption of carbon particles at infrared 880 nm, were operated at time interval of 5-min between January 9 and February 10, 2010 at an urban site of Gwangju, to compare the accuracy of black carbon (BC) concentrations reported from the AE-51 model and to investigate reasonable sampling time of filter media in the AE-51. The air samples in the AE-51 and AE-16 models are collected on T60 (Teflon coated glass fiber) filter media (filter spot area: 0.07 $cm^2$) and quartz fiber roll-tape filter (filter spot area: 1.67 $cm^2$), respectively. Real-time measurement results indicate that when the filters were clean, the AE-51 BC was greater than or similar to the AE-16 BC data. However as the filter spots become darker, the AE-16 BC concentrations were higher than the AE-51 BC data and the difference in the BC concentrations from two AE models becomes gradually increased. Relative error in the AE-51 and AE-16 BC concentrations showed significance difference depending on used time of the filter in the AE-51 model, weather pattern, levels of air pollution, etc, ranging from 11.5% (used time of the filter in AE-51: 1,595 min) to 52.5% (used time of the filter in AE-51: 2,085 min). When considering the used time of one filter ticket in the AE-51 model and difference (or relative error %) between AE-16 and AE-51 BC concentrations, it is recommended that the standard sampling time per one filter ticket within the AE-51 model be less than approximately 24 hr (1,440 min) under the normal weather conditions except for severe haze and mist events.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.709-720
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• 2018

In order to optimize the evaluation of biomass in crop monitoring, accurate and timely data of the crop-field are required. Evaluating above-ground biomass helps to monitor crop vitality and to predict yield. Unmanned Aerial Vehicle (UAV) imagery are being assessed for analyzing within field spatial variability for agricultural precision management, because UAV imagery may be acquired quickly during critical periods of rapid crop growth. This study reports on the development of remote sensing techniques for evaluating the biomass of winter crop. Specific objective was to develop statistical models for estimating the dry weight of barley and wheat using a Excess Green index ($E{\times}G$) based Vegetation Fraction (VF) and a Crop Surface Model (CSM) based Plant Height (PH) value. As a result, the multiple linear regression equations consisting of three independent variables (VF, PH, and $VF{\times}PH$) and above-ground dry weight provided good fits with coefficients of determination ($R^2$) ranging from 0.86 to 0.99 with 5 cultivars. In the case of the barley, the coefficient of determination was 0.91 and the root mean squared error of measurement was $102.09g/m^2$. And for the wheat, the coefficient of determination was 0.90 and the root mean squared error of measurement was $110.87g/m^2$. Therefore, it will be possible to evaluate the biomass of winter crop through the UAV image for the crop growth monitoring.

• Journal of Korean Ophthalmic Optics Society
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• v.2 no.1
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• pp.77-83
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• 1997

This study was carried out to investigate the effect of environmental factors on 380 children's unaided visual acuity and to determine the visual acuity and objective refraction error of these children. The unaided visual acuity and objective refraction error were measured by the TOPCON chart projector and refractometer on 147 kindergarteners and 233 primary school children ranging from age 5 to 12. The measurement on the unaided visual acuity of children were 3% for below the 0.1 visual acuity 9% for 0.1~0.4. 18% for 0.5~0.7. 16% for 0.8~0.9. and 54% for over 1.0 visual acuity respectively. The refractive errors were 9.35% for mixed astigmatism. 14.5% for hyperopia 75.88% for myopia. and 0.27% for emmetropia. respectively. When analyzing the environmental factors. the relationship between the children's visual acuity and the number of hours the children watched TV. the more hours they watched TV. the more the children lost their visual acuity. The visual acuity of children decreased abruptly in the groups that watched TV more than 4 hour a day. When comparing the relationship between the children's visual acuity and proximity to the TV, the further away from the TV they were the higher visual acuity. There is rna relation between the children's visual acuity and the studying hour or reading hour of children. The relationship between the children's visual acuity and their dwelling environment, the visual acuity of children who lived in an independent house were better than the visual acuity of children who dwelled in an apartment.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.361-373
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• 2013

The monitoring of urban area, target detection and building reconstruction have been actively studied and investigated since high resolution X-band SAR images could be acquired by airborne and/or satellite SAR systems. This paper describes an efficient approach to reconstruct artificial structures (e.g. apartment, building and house) in urban area using high resolution X-band SAR images. Building footprint was first extracted from 1:25,000 digital topographic map and then a corner line of building was detected by an automatic detecting algorithm. With SAR amplitude images, an initial building height was calculated by the length of layover estimated using KS-test (Kolmogorov-Smirnov test) from the corner line. The interferometric SAR phases were simulated depending on SAR geometry and changable building heights ranging from -10 m to +10 m of the initial building height. With an interferogram from real SAR data set, the simulation results were compared using the method of the phase consistency. One of results can be finally defined as the reconstructed building height. The developed algorithm was applied to repeat-pass TerraSAR-X spotlight mode data set over an apartment complex in Daejeon city, Korea. The final building heights were validated against reference heights extracted from LiDAR DSM, with an RMSE (Root Mean Square Error) of about 1~2m.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.40 no.10
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• pp.629-636
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• 2016

This study presents the development of an acid resistance velocity sensor that is used for measuring velocity inside a copper sulfate plating bath. First, researchers investigated the acid resistance coating to confirm the suitability of the anti-acid sensor in a very corrosive environment. Then, researchers applied signal processing methods to reduce noise and amplify the signal. Next, researchers applied a pressure-resistive sensor with an operation amplifier (Op Amp) and low-pass filter with high impedance to match the output voltage of a commercial flowmeter. Lastly, this study compared three low-pass filters (Bessel, Butterworth and Chebyshev) to select the appropriate signal process circuit. The results show 0.0128, 0.0023, and 5.06％ of the mean square error, respectively. The Butterworth filter yielded more precise results when compared to a commercial flowmeter. The acid resistive sensor is capable of measuring velocities ranging from 2 to 6 m/s with a 2.7％ margin of error.

• Journal of Korea Water Resources Association
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• v.33 no.4
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• pp.471-482
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• 2000

Surface energy balance components were evaluated by Landsat TM data and GIS with meteorological data. Calibration and validation for the applicability of this methodology were made through the estimating of the large-scale evapotranspiration (ET). In addition, sensitivity and error analysis was conducted to see the effects of the surface energy balance components on ET and the accuracy of each components. Bochong-chon located on the upper part of Guem River basin was selected as the case study area. Spatial distribution map of ET were produced for five dates: Jan. 1, Apr. 3, May. 10, and Nov. 27, 1995. The study results showed tat ET was greatly varied with the aspect and theland use type on the surface. In the case of having northeast and southeast in the aspect, ET was linearly increased depending on growing net radiation. While surface temperature has a high value, NDVI(Normalized Difference Vegetation Index) has a low value in the vegetated area. Therefore, ground heat flux was increased but ET was relatively decreased. The results of sensitivity and error analysis showed that net radiation is most sensitive and effective, ranging from 12.5% to 23.6% of sensitivity. Furthermore, the surface temperature, air temperature, and wind speed have the significant effects on ET estimation using remotely sensed data.

• Korean Journal of Optics and Photonics
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• v.11 no.2
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• pp.73-79
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• 2000

We measure a beam diameter of scan and sub-scan direction of LSD (Laser Scanning Urnt) which uses $fheta$ lens produced by injecLion molding method as a scanning lens. While the measured beam diameter in scan direction, which is $62muextrm{m}$ to $68\mu\textrm{m}$, shows similar size comparing to the design beam diameter, the sub-scan beam diameter shows sIzable beam diameter deviation as much as 37 11m ranging from $78\mu\textrm{m}$ to $115\mu\textrm{m}$. Injection molding lens has the surface figure error due to the shrinkage III the cooling time and the internal distortion (birefringence) due to the uneven cooling conditIOn so that these bring about wavefront aberration (i.e., the enlargement of beam size), and are eventually expre~sed as the deterioration of the pdnting image. In this paper. we first measure and analyze beam diameter, birefringence (polanzation ratio), and asphedcal figure error of mIens in order to know the principle cause of the beam diameter deviation in sub-scan directIOn. And Lhen. through the analysis of a designed depth of focus and a calculated field curvature (imaging position of the optical axis directIon) using the above figure elTor data, we know Lhat the birefringence IS the main factor of sizable beam diameter deVIation in sub-scan direction. ction.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.841-850
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• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.