• Journal of Biosystems Engineering
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• v.38 no.4
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• pp.312-317
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• 2013

Purpose: Conventional methods used to evaluate seeds viability are destructive, time consuming, and require the use of chemicals, which are not feasible to implement to process plant in seed industry. In this study, the effectiveness of Fourier transform near infrared (FT-NIR) spectroscopy to differentiate between viable and nonviable watermelon seeds was investigated. Methods: FT-NIR reflectance spectra of both viable and non-viable (aging) seeds were collected in the range of 4,000 - 10,000 $cm^{-1}$ (1,000 - 2,500 nm). To differentiate between viable and non-viable seeds, a multivariate classification model was developed with partial least square discrimination analysis (PLS-DA). Results: The calibration and validation set derived from the PLS-DA model classified viable and non-viable seeds with 100% accuracy. The beta coefficient of PLS-DA, which represented spectral difference between viable and non-viable seeds, showed that change in the chemical component of the seed membrane (such as lipids and proteins) might be responsible for the germination ability of the seeds. Conclusions: The results demonstrate the possibility of using FT-NIR spectroscopy to separate seeds based on viability, which could be used in the development of an online sorting technique.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.9
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• pp.103-112
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• 1999

In this paper, a speaker-independent isolated world recognition system for a car navigation system is implemented using a general digital signal processor. This paper presents a method combining SNR normalization with RAS as a noise processing method. The semi-continuous hidden markov model is adopted and TMS320C31 is used in implementing the real-time system. Recognition word set is composed of 69 command words for a car navigation system. Experimental results showed that the recognition performance has a maximum of 93.62% in case of a combination of SNR normalization and spectral subtraction, and the performance improvement rate of the system is 3.69%, Presented noise processing method showed good speech recognition performance in 5dB SNR in car environment.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.164-169
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• 2017

The primary purpose of this study is to determine NDVI analysis methodologies for green algae monitoring system. A fixed wing UAV integrated with multi-spectral sensor has been adopted to capture the images along the watershed in Gumgang River. The study area was near the Baekje water reservoir and the images was captured on July 2016. Pix4D Mapper Pro was used to process the captured images. Through the comparison actual chlorophyll measurement values with NDVI output image, empirical formula was suggested and geo-locational conversion was carried out. As a result of this study chlorophyll image set applied to actual measurement values was able to extracted. For the efficient management of green algae, its monitoring and prevention in terms of disaster management, gathering chlorophyll information using UAV is very beneficial.

• Journal of the Korean Chemical Society
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• v.47 no.1
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• pp.19-25
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• 2003

A spectrophotometric method for the simultaneous determination of anionic and nonionic surfactant based on the application of multivariate calibration method such as principal component regression(PCR) and partial least squares(PLS) has been studied. The calibration models in PCR and PLS were obtained from the spectral data in the range of 400~700 nm for each standard of a calibration set of 26 standards, each containing different amounts of two surfactants. The relative standard error of prediction(RSEP$_{\alpha}$) was obtained to assess the model goodness in quantifying each analyte in a 5 validation samples which containing different amounts of two surfactants.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.777-786
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• 2018

This study propose a new method to detect Cochlodinium polykrikoides on satellite images using logistic regression and decision tree. We used spectral profiles(918) extracted from red tide, clear water and turbid water as training data. The 70% of the entire data set was extracted and used for model training, and the classification accuracy of the model was evaluated by using the remaining 30%. As a result of the accuracy evaluation, the logistic regression model showed about 97% classification accuracy, and the decision tree model showed about 86% classification accuracy.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.2
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• pp.208-214
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• 2012

The spectral radiance received by a remote sensor is consisted of the self-emitted component directly from the target surface, the reflected component of the solar irradiance at the target surface, and the scattered component by the atmosphere without ever reaching the object surface. In general, the self-emitted component is the most important part in the infrared signatures from the target. We measured the solar irradiation, sky irradiation, air temperature, wind velocity, wind direction, relative humidity, and atmospheric pressure together with the surface temperatures of rectangular parallelepiped targets. The measured diurnal surface temperature variations on the three different rectangular parallelepiped targets constructed by the steel, aluminum and bakelite are obtained at the same time intervals. The measured surface temperature results show that the top surface temperature of bakelite recorded up tp $7.6^{\circ}C$ higher than that of aluminium and $6.1^{\circ}C$ higher than that of steel at 11 AM on the sunny condition. A complete set of measured data including the surface temperature of rectangular parallelepiped targets together with the detailed weather information can be a valuable reference for future study.

• Journal of Biosystems Engineering
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• v.38 no.1
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• pp.48-54
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• 2013

Purpose: This study evaluated the feasibility of using a discrete wavelet transform (DWT) method as a preprocessing tool for visible/near-infrared spectroscopy (VIS/NIRS) with a spectroscopic transmittance dataset for predicting the internal quality of cherry tomatoes. Methods: VIS/NIRS was used to acquire transmittance spectrum data, to which a DWT was applied to generate new variables in the wavelet domain, which replaced the original spectral signal for subsequent partial least squares (PLS) regression analysis and prediction modeling. The DWT concept and its importance are described with emphasis on the properties that make the DWT a suitable transform for analyzing spectroscopic data. Results: The $R^2$ values and root mean squared errors (RMSEs) of calibration and prediction models for the firmness, sugar content, and titratable acidity of cherry tomatoes obtained by applying the DWT to a PLS regression with a set of spectra showed more enhanced results than those of each model obtained from raw data and mean normalization preprocessing through PLS regression. Conclusions: The developed DWT-incorporated PLS models using the db5 wavelet base and selected approximation coefficients indicate their feasibility as good preprocessing tools by improving the prediction of firmness and titratable acidity for cherry tomatoes with respect to $R^2$ values and RMSEs.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.195-198
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• 2012

The N basis functions are typically chosen so that Surface reflectance functions(SRFs) and spectral power distributions (SPDs) can be accurately reconstructed from their N-dimensional vector codes. Typical rendering applications assume that the resulting mapping is an isomorphism where vector operations of addition, scalar multiplication, component-wise multiplication on the N-vectors can be used to model physical operations such as superposition of lights, light-surface interactions and inter-reflection. The vector operations do not mirror the physical. However, if the choice of basis functions is restricted to characteristic functions then the resulting map between SPDs/SRFs and N-vectors is anisomorphism that preserves the physical operations needed in rendering. This paper will show how to select optimal characteristic function bases of any dimension N (number of basis functions) and also evaluate how accurately a large set of Munsell color chips can approximated as basis functions of dimension N.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.229-234
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• 2002

Under the hostile influence of the extreme space environmental conditions due to the deep space and direct solar flux, the thermal control in space applications is especially of major importance. There are tight temperature range restrictions for electro-optical elements while on the other hand there are low power consumption requirements due to the limited energy sources on the spacecraft. So, we usually have strong requirement of thermal and power control module in space applications. In this paper, the design concept of a thermal and power control module in the MSC(Multi-Spectral Camera) system which will be a payload on KOMPSATII is described in terms of H/W & S/W. This thermal and power control module, called THTM(Thermal and Telemetry Module) in MSC, resides inside the PMU(Payload Management Unit) which is responsible for the proper management of the MSC payload for controlling and monitoring the temperature insides the EOS(Electro-Optic System) and gathering all the analog telemetry from all the MSC sub-units, etc. Particularly, the designed heater controller has the special mode of "duty cycle" in addition to normal closed loop control mode as usual. THTM controls heaters in open loop according to on/off set time designed through analysis in duty cycle mode in case of all thermistor failure whereas it controls heaters by comparing the thermistor value to temperature based on closed loop in normal mode. And a designed THTM provides a checking and protection method against the failure in thermal control command using the test pulse in command itself.

• Nuclear Engineering and Technology
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• v.52 no.1
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• pp.192-205
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• 2020

Seismic design practices and seismic response analyses of civil structures and nuclear power plants (NPPs) have conventionally used the peak ground acceleration (PGA) or spectral acceleration (S_a) as an intensity measure (IM) of an earthquake. However, there are many other earthquake IMs that were proposed by various researchers. The aim of this study is to investigate the correlation between seismic responses of NPP components and 23 earthquake IMs and identify the best IMs for correlating with damage of NPP structures. Particularly, low- and high-frequency ground motion records are separately accounted in correlation analyses. An advanced power reactor NPP in Korea, APR1400, is selected for numerical analyses where containment and auxiliary buildings are modeled using SAP2000. Floor displacements and accelerations are monitored for the non- and base-isolated NPP structures while shear deformations of the base isolator are additionally monitored for the base-isolated NPP. A series of Pearson's correlation coefficients are calculated to recognize the correlation between each of the 23 earthquake IMs and responses of NPP structures. The numerical results demonstrate that there is a significant difference in the correlation between earthquake IMs and seismic responses of non-isolated NPP structures considering low- and high-frequency ground motion groups. Meanwhile, a trivial discrepancy of the correlation is observed in the case of the base-isolated NPP subjected to the two groups of ground motions. Moreover, a selection of PGA or S_a for seismic response analyses of NPP structures in the high-frequency seismic regions may not be the best option. Additionally, a set of fragility curves are thereafter developed for the base-isolated NPP based on the shear deformation of lead rubber bearing (LRB) with respect to the strongly correlated IMs. The results reveal that the probability of damage to the structure is higher for low-frequency earthquakes compared with that of high-frequency ground motions.