• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.5
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• pp.149-156
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• 2021

FRP has been proposed to replace the steel as a reinforcement in the concrete structures for addressing the corrosion issue. However, FRP-Rebar does not behave in the same manner as steel because the properties of FRP are different. For example, FRP-Rebar has a high tensile strength, low stiffness, and linear elastic behavior which results in a difference bonding mechanism to transfer the load between the reinforcement and the surrounding concrete. Therefore, bonding behavior between FRP-Rebar and concrete has to be investigated using the bonding test. So, Pull-out test has been used to estimate bond behavior because it is simple. However, the results of pull-out test have a difference with flexural-boding behavior of FRP-Rebar concrete member. So, it is needed to evaluate the real fleuxral-bonding behavior. In this study, the evaluation method to flexural-bonding behavior of FRP-Rebar concrete member was reviewed and compared. It was found that the most accurate evaluation method for the fleuxral-bonding behavior of FRP-Rebar concrete member was splice beam test, however, the size and length of specimen have to increase than other test method and the design and analysis of splice beam is complex. Meanwhile, characteristics of concrete could be reflected by using arched beam test, unlike hinged beam test which is based on the ignored change of moment arm length in equilibrium equation. However, the possibility of shear failure exists before the flexural-bonding failure occur.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.253-260
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• 2019

Radiation dose enhancement is a method of increasing the cross section of interaction, thus increasing the deposited dose. This can contribute to linear energy transfer, LET and relative biological effectiveness, RBE. Previous studies on dose enhancement have been mainly focused on X, ${\gamma}-rays$, but in this study, the dose enhancement was analyzed for proton using Monte Carlo simulation using MCNP6. Based on the mathematical modeling method, energy spectrum and relative intensity of spread out Bragg-peak were calculated, and evaluated dose enhancement factor and dose distribution of dose enhancement material, such as aurum and gadolinium. Dose enhancement factor of 1.085-1.120 folds in aurum, 1.047-1.091 folds in gadolinium was shown. In addition, it showed a decrease of 95% modulation range and practical range. This may lead to an uncertain dose in the tumor tissue as well as dose enhancement. Therefore, it is necessary to make appropriate corrections for spread out Bragg-peak and practical range from mass stopping power. It is expected that Monte Carlo simulation for dose enhancement will be used as basic data for in-vivo and in-vitro experiments.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.203-215
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• 2019

As hyperspectral sensors that can be mounted on drones are developed, it is possible to acquire hyperspectral imagery with high spatial and spectral resolution. Although the importance of atmospheric correction has been reduced since imagery of drones were acquired at a low altitude,studies on the conversion process from raw data to spectral reflectance should be done for studies such as estimating the concentration of surface materials using hyperspectral imagery. In this study, a vicarious radiometric calibration and an atmospheric correction algorithm based on atmospheric radiation transfer model were applied to hyperspectral data of drone and the results were compared and analyzed. The vicarious calibration method was applied to an empirical line calibration using the spectral reflectance of a tarp made of uniform material. The atmospheric correction algorithm used ATCOR-4 based Modran-5 that was widely used for the atmospheric correction of aerial hyperspectral imagery. As a result of analyzing the RMSE of the difference between the reference reflectance and the correction, the vicarious calibration using the tarp in a single period of hyperspectral image was the most accurate, but the atmospheric correction was possible according to the application purpose of using hyperspectral imagery. If the correction process of normalized spectral reflectance is carried out through the additional vicarious calibration for imagery from multiple periods in the future, accurate analysis using hyperspectral drone imagery will be possible.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1210-1210
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• 2001

On farm analysis of protein, moisture and oil in cereals and oil seeds is quickly being adopted by Australian farmers. The benefits of being able to measure protein and oil in grains and oil seeds are several : $\square$ Optimize crop payments $\square$ Monitor effects of fertilization $\square$ Blend on farm to meet market requirements $\square$ Off farm marketing - sell crop with load by load analysis However farmers are not NIR spectroscopists and the process of calibrating instruments has to the duty of the supplier. With the potential number of On Farm analyser being in the thousands, then the task of calibrating each instrument would be impossible, let alone the problems encountered with updating calibrations from season to season. As such, NIR technology Australia has developed a mechanism for \ulcorner\ulcorner\ulcorner their range of Cropscan 2000G NIR analysers so that a single calibration can be transferred from the master instrument to every slave instrument. Whole grain analysis has been developed over the last 10 years using Near Infrared Transmission through a sample of grain with a pathlength varying from 5-30mm. A continuous spectrum from 800-1100nm is the optimal wavelength coverage fro these applications and a grating based spectrophotometer has proven to provide the best means of producing this spectrum. The most important aspect of standardizing NIB instruments is to duplicate the spectral information. The task is to align spectrum from the slave instruments to the master instrument in terms of wavelength positioning and then to adjust the spectral response at each wavelength in order that the slave instruments mimic the master instrument. The Cropscan 2000G and 2000B Whole Grain Analyser use flat field spectrographs to produce a spectrum from 720-1100nm and a silicon photodiode array detector to collect the spectrum at approximately 10nm intervals. The concave holographic gratings used in the flat field spectrographs are produced by a process of photo lithography. As such each grating is an exact replica of the original. To align wavelengths in these instruments, NIR wheat sample scanned on the master and the slave instruments provides three check points in the spectrum to make a more exact alignment. Once the wavelengths are matched then many samples of wheat, approximately 10, exhibiting absorbances from 2 to 4.5 Abu, are scanned on the master and then on each slave. Using a simple linear regression technique, a slope and bias adjustment is made for each pixel of the detector. This process corrects the spectral response at each wavelength so that the slave instruments produce the same spectra as the master instrument. It is important to use as broad a range of absorbances in the samples so that a good slope and bias estimate can be calculated. These Slope and Bias (S'||'&'||'B) factors are then downloaded into the slave instruments. Calibrations developed on the master instrument can then be downloaded onto the slave instruments and perform similarly to the master instrument. The data shown in this paper illustrates the process of calculating these S'||'&'||'B factors and the transfer of calibrations for wheat, barley and sorghum between several instruments.

• Journal of the Korean Electrochemical Society
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• v.26 no.3
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• pp.35-41
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• 2023

The carbon-coated silicon monoxide (c-SiO_x), which is a negative electrode active material for lithium-ion batteries (LIBs), has a limited cycle performance due to severe volume changes during cycles, despite its high specific capacity. In particular, the significant volume change of the active material can deform the electrode structure and easily damage the electron transfer pathway. To improve performance and mitigate electrode damage caused by volume changes, we replaced parts of the carbon black conducting agent with carbon nanotubes (CNTs) having a linear shape. The content of the entire conductive material in the electrode was fixed at 10% by mass, and the relative content of CNTs ranged from 0% to 25% by mass to prepare electrodes and evaluate electrochemical performance. As the CNT content in the electrode increased, both cycle life and rate capability improved. Even a small amount of CNT can significantly improve the electrochemical performance of a c-SiO_x negative electrode with large volume changes. Furthermore, dispersing CNTs effectively can lead to achieving the equivalent performance with a reduced quantity of CNTs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.157-164
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• 2023

This paper suggests O(n²) polynomial time heuristic algorithm for corporate tax structure optimization problem that has been classified as NP-complete problem. The proposed algorithm constructs tax tree levels that the target holding company is located at root node of Level 1, and the tax code categories(T_e) 1,4,3,2 are located in each level 2,3,4,5 sequentially. To find the maximum tax-relief path from source(S) to target(T), firstly we connect the minimum witholding tax rate _minr_w(u, v) arc of node u point of view for transfer the profit from u to v node. As a result we construct the spanning tree from all of the source nodes to a target node, and find the initial feasible solution. Nextly, we find the alternate path with minimum foreign tax rate _minr_fi(u, v) of v point of view. Finally we choose the minimum tax-relief path from of this two paths. The proposed heuristic algorithm performs better optimal results than linear programming and Tabu search method that is a kind of metaheuristic method.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.355-361
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• 2023

Temperature of the Earth's surface is a crucial physical variable in understanding weather and atmospheric dynamics and in coping with extreme heat events that have a great impact on living organismsincluding humans. Thermalsensors on satellites have been a useful meansfor acquiring surface temperature information for wide areas on the globe, and thus characterization of its estimation uncertainty is of central importance for the utilization of the data. Among various factors that affect the estimation, the uncertainty caused by the algorithm itself has not been tested for the atmospheric environment of Korean vicinity. Thisstudy derivesthe uncertainty of the single-channel algorithm under the local atmospheric and oceanic conditions by using reanalysis data and buoy temperature data collected around Korea. Atmospheric profiles were retrieved from two types of reanalysis data, the fifth generation of European Centre for Medium-Range Weather Forecasts reanalysis of the global climate and weather (ERA5) and Modern-Era Retrospective analysis for Research and Applications-2 (MERRA-2) to investigate the effect of reanalysis data. MODerate resolution atmospheric TRANsmission (MODTRAN) was used as a radiative transfer code for simulating top of atmosphere radiance and the atmospheric correction for the temperature estimation. Water temperatures used for MODTRAN simulations and uncertainty estimation for the single-channel algorithm were obtained from marine weather buoyslocated in seas around the Korean Peninsula. Experiment results showed that the uncertainty of the algorithm varies by the water vapor contents in the atmosphere and is around 0.35K in the driest atmosphere and 0.46K in overall, regardless of the reanalysis data type. The uncertainty increased roughly in a linear manner as total precipitable water increased.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.458-467
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• 2010

In this paper, a new audio reproduction system was developed in which the cross-talk signals would be reasonably cancelled at an arbitrary listener position. To adaptively remove the cross-talk signals according to the listener's position, a method of tracking the listener position was employed. This was achieved using the two microphones, where the listener direction was estimated using the time-delay between the two signals from the two microphones, respectively. Moreover, room reverberation effects were taken into consideration where linear prediction analysis was involved. To remove the cross-talk signals at the left-and right-ears, the paths between the sources and the ears were represented using the KEMAR head-related transfer functions (HRTFs) which were measured from the artificial dummy head. To evaluate the usefulness of the proposed listener tracking system, the performance of cross-talk cancellation was evaluated at the estimated listener positions. The performance was evaluated in terms of the channel separation ration (CSR), a -10 dB of CSR was experimentally achieved although the listener positions were more or less deviated. A real-time system was implemented using a floating-point digital signal processor (DSP). It was confirmed that the average errors of the listener direction was 5 degree and the subjects indicated that 80 % of the stimuli was perceived as the correct directions.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.127-146
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• 2022

Recently, as word embedding has shown excellent performance in various tasks of deep learning-based natural language processing, researches on the advancement and application of word, sentence, and document embedding are being actively conducted. Among them, cross-language transfer, which enables semantic exchange between different languages, is growing simultaneously with the development of embedding models. Academia's interests in vector alignment are growing with the expectation that it can be applied to various embedding-based analysis. In particular, vector alignment is expected to be applied to mapping between specialized domains and generalized domains. In other words, it is expected that it will be possible to map the vocabulary of specialized fields such as R&D, medicine, and law into the space of the pre-trained language model learned with huge volume of general-purpose documents, or provide a clue for mapping vocabulary between mutually different specialized fields. However, since linear-based vector alignment which has been mainly studied in academia basically assumes statistical linearity, it tends to simplify the vector space. This essentially assumes that different types of vector spaces are geometrically similar, which yields a limitation that it causes inevitable distortion in the alignment process. To overcome this limitation, we propose a deep learning-based vector alignment methodology that effectively learns the nonlinearity of data. The proposed methodology consists of sequential learning of a skip-connected autoencoder and a regression model to align the specialized word embedding expressed in each space to the general embedding space. Finally, through the inference of the two trained models, the specialized vocabulary can be aligned in the general space. To verify the performance of the proposed methodology, an experiment was performed on a total of 77,578 documents in the field of 'health care' among national R&D tasks performed from 2011 to 2020. As a result, it was confirmed that the proposed methodology showed superior performance in terms of cosine similarity compared to the existing linear vector alignment.

• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.31-42
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• 2009

Purpose: As the number of domestic medical institutions installing PET/CT is increasing rapidly, the transfer of PET/CT images among medical institutions is also increasing. Thus, it is necessary to collect the comparative SUV data from several medical institutions' PET/CT systems through a phantom study which semi-quantitatively compares the SUV on one bed, the change scale of the SUV on the slices, and the time of measuring. The phantom study to find differences among the SUVs from various PET/CT offers the opportunity to obtain the reliability of the SUV in PET/CT images. Materials and Methods: Ten PET/CT systems from medical institutions in Korea were used. To obtain the accurate data, the study has been using the radiation detector of Korea Research Institute of Standards and Science to verify. The internal structures of NEMA $phantom^{TM}$ were removed and Six thousand milliliters of distilled water which has 1mCi of $^{18}F$-FDG put into the phantom. The water was properly integrated with $^{18}F$-FDG using magnetic stirrer. The images were acquired at 60, 70, 80, 90, 100, 110 and 120-minutes for 3 minute each. Two hundred square centimeters of region of interests were placed and analyzed. To confirm the usefulness, the correction-table came out from patients' data. Results: The coefficient of variability of the SUV from -11.0 to 9.90 % fell into the range of international standards(${\pm}10%$) along with the SUV on a bed, the change scale of the SUV on the slices, and the time of measuring, except one PET/CT system. Using the data of the differences among the SUVs, we came to withdraw the correction-table ranging from 0.803 to 1.246. The correction-table was confirmed its usefulness through Linear Regression Analysis which was applied to normal cases. Conclusions: Although studies have been made on the variation of the SUV, there is little attention on the standardization of the SUV. Based on this study of the quantitatively comparable data about the SUV accommodating the correction-table, it would help to have more corrective diagnosis.