• Proceedings of the KSRS Conference
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• 2008.03a
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• pp.195-200
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• 2008

The accuracy of classifying pixels in HIRIS images is usually degraded by noisy bands since noisy bands may deform the typical shape of spectral reflectance. Proposed in this paper is a statistical method for noisy band removal which mainly makes use of the correlation coefficients between bands. Considering each band as a random variable, the correlation coefficient measures the strength and direction of a linear relationship between two random variables. While the correlation between two signal bands is high, existence of a noisy band will produce a low correlation due to ill-correlativeness and undirectedness. The application of the correlation coefficient as a measure for detecting noisy bands is under a two-pass screening scheme. This method is independent of the prior knowledge of the sensor or the cause resulted in the noise. The classification in this experiment uses the unsupervised k-nearest neighbor algorithm in accordance with the well-accepted Euclidean distance measure and the spectral angle mapper measure. This paper also proposes a hierarchical combination of these measures for spectral matching. Finally, a separability assessment based on the between-class and within-class scatter matrices is followed to evaluate the performance.

• Journal of Electrochemical Science and Technology
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• v.7 no.3
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• pp.218-227
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• 2016

The light harvesting efficiency is counted as an important factor in the power conversion efficiency of DSSCs. There are two measures to improve this parameter, including enhancing the dye-loading capacity and increasing the light trapping in the photoanode structure. In this paper, these tasks are addressed by introducing a macro-porous silicon (PSi) substrate as photoanode. The effects of the novel photoanode structure on the DSSC performance have been investigated by using energy dispersive X-ray spectroscopy, photocurrent-voltage, UV-visible spectroscopy, reflectance spectroscopy, and electrochemical impedance spectroscopy measurements. The results indicated that bigger porosity percentage of the PSi structure improved the both anti-reflective/light-trapping and dye-loading capacity properties. PSi based DSSCs own higher power conversion efficiency due to its remarkable higher photocurrent, open circuit voltage, and fill factor. Percent porosity of 64%, PSi(III), resulted in nearly 50 percent increment in power conversion efficiency compared with conventional DSSC. This paper showed that PSi can be a good candidate for the improvement of light harvesting efficiency in DSSCs. Furthermore, this study can be considered a valuable reference for more investigations in the design of multifunctional devices which will profit from integrated on-chip solar power.

• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.141-150
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• 2018

Crop type classification is essential for supporting agricultural decisions and resource monitoring. Remote sensing techniques, especially using hyperspectral imagery, have been effective in agricultural applications. Hyperspectral imagery acquires contiguous and narrow spectral bands in a wide range. However, large dimensionality results in unreliable estimates of classifiers and high computational burdens. Therefore, reducing the dimensionality of hyperspectral imagery is necessary. In this study, the Random Forest (RF) classifier was utilized for dimensionality reduction as well as classification purpose. RF is an ensemble-learning algorithm created based on the Classification and Regression Tree (CART), which has gained attention due to its high classification accuracy and fast processing speed. The RF performance for crop classification with airborne hyperspectral imagery was assessed. The study area was the cultivated area in Chogye-myeon, Habcheon-gun, Gyeongsangnam-do, South Korea, where the main crops are garlic, onion, and wheat. Parameter optimization was conducted to maximize the classification accuracy. Then, the dimensionality reduction was conducted based on RF variable importance. The result shows that using the selected bands presents an excellent classification accuracy without using whole datasets. Moreover, a majority of selected bands are concentrated on visible (VIS) region, especially region related to chlorophyll content. Therefore, it can be inferred that the phenological status after the mature stage influences red-edge spectral reflectance.

• Korean Journal of Materials Research
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• v.30 no.3
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• pp.131-135
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• 2020

Silver nanowire (AgNW) networks have been adopted as a front electrode in Cu(In,Ga)Se2 (CIGS) thin film solar cells due to their low cost and compatibility with the solution process. When an AgNW network is applied to a CIGS thin film solar cell, reflection loss can increase because the CdS layer, with a relatively high refractive index (n ~ 2.5 at 550 nm), is exposed to air. To resolve the issue, we apply solution-processed ZnO nanorods to the AgNW network as an anti-reflective coating. To obtain high performance of the optical and electrical properties of the ZnO nanorod and AgNW network composite, we optimize the process parameters - the spin coating of AgNWs and the concentration of zinc nitrate and hexamethylene tetramine (HMT - to fabricate ZnO nanorods. We verify that 10 mM of zinc nitrate and HMT show the lowest reflectance and 10% cell efficiency increase when applied to CIGS thin film solar cells.

• Bulletin of the Korean Chemical Society
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• v.31 no.10
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• pp.2909-2912
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• 2010

Hydrogenated microcrystalline silicon (${\mu}c$-Si:H) thin film for solar cells is prepared by plasma-enhanced chemical vapor deposition and physical properties of the ${\mu}c$-Si:H p-layer has been investigated. With respect to stable efficiency, this film is expected to surpass the performance of conventional amorphous silicon based solar cells and very soon be a close competitor to other thin film photovoltaic materials. Silicon in various structural forms has a direct effect on the efficiency of solar cell devices with different electron mobility and photon conversion. A Raman microscope is adopted to study the degree of crystallinity of Si film by analyzing the integrated intensity peaks at 480, 510 and $520\;cm^{-1}$, which corresponds to the amorphous phase (a-Si:H), microcrystalline (${\mu}c$-Si:H) and large crystals (c-Si), respectively. The crystal volume fraction is calculated from the ratio of the crystalline and the amorphous phase. The results are compared with high-resolution transmission electron microscopy (HR-TEM) for the determination of crystallinity factor. Optical properties such as refractive index, extinction coefficient, and band gap are studied with reflectance spectra.

• Fashion & Textile Research Journal
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• v.8 no.1
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• pp.134-138
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• 2006

The washing efficiency of two types of washing machine- drum(drum washing) and drum using steam jet system(steam drum washing) was studied. The purpose of this paper is to clarify the performance of new steam drum washing. The relationship between washing temperature and washing efficiency(reflectance(%)) by soil removal, and that between washing temperature and electric energy consumption, Fabric damage evaluated by Danish wear method, Fabric shrinkage(%) during laundering were investigated, and compared with those in drum washing machine. Washing efficiency of steam drum washing according to washing temperature is better than that of drum washing. Electric energy consumption and fabric damage in steam drum washing are lower than those of drum washing. Fabric damage increased as washing temperature increased. Shrinkage of fabrics in steam drum washing and drum washing are about same. Therefore, we assumed that in the case of steam drum washing using steam jet system, washing efficiency remarkably increased, and fabric damage decreased, even with a lot of saving in given electric energy and water used.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.190-190
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• 2010

Zinc oxide is the most attractive material due to the large direct band gap (3.37 eV), excellent chemical and thermal stability, and large exciton binding energy (60 meV). Recently, ZnO nanorods were used as the high efficient antireflection coating layer of solar cells based on silicon (Si). In this reports, we studied the effects of rapid thermal annealing (RTA) treatment on optical properties of ZnO nanorods. For fabrication of ZnO nanorods, there are many methods such as hydrothermal method, sol-gel method, and metal organic chemical vapor deposition method. Among of them, we used the conventional wet chemical method which is simple and low temperature growth. In order to synthesize the ZnO nanorods, the ZnO films were deposited on Si substrate by RF magnetron sputtering at room temperature and the samples were dipped to aqua solution containing the zinc nitrate and hexamethylentetramines (HMT). The synthesis process was achieved in keeping with temperature of $90-95^{\circ}C$ and under constant stirring. The morphology of ZnO nanorods on glass and Si was characterized by scanning electron microscopy. For the analysis of antireflection performance, the reflectance and transmittance were measured by spectrophotometer. And for analyzing the effects of RTA treatment on ZnO nanorods, crystalline properties were investigated by X-ray diffraction measurements and optical properties was estimated by photoluminescence spectra.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.263-270
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• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.21-32
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• 2007

Fire fuel map is one of the most critical factors for planning and managing the fire hazard and risk. However, fuel mapping is extremely difficult because fuel properties vary at spatial scales, change depending on the seasonal situations and are affected by the surrounding environment. Remote sensing has potential to reduce the uncertainty in mapping fuels and offers the best approach for improving our abilities. Especially, Hyperspectral sensor have a great potential for mapping vegetation properties because of their high spectral resolution. The objective of this paper is to evaluate the potential of mapping fuel properties using Hyperion hyperspectral remote sensing data acquired in April, 2002. Fuel properties are divided into four broad categories: 1) fuel moisture, 2) fuel green live biomass, 3) fuel condition and 4) fuel types. Fuel moisture and fuel green biomass were assessed using canopy moisture, derived from the expression of liquid water in the reflectance spectrum of plants. Fuel condition was assessed using endmember fractions from spectral mixture analysis (SMA). Fuel types were classified by fuel models based on the results of SMA. Although Hyperion imagery included a lot of sensor noise and poor performance in liquid water band, the overall results showed that Hyperion imagery have good potential for wildfire fuel mapping.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.35-42
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• 2002

The results of our observation in May 2000 indicated that the SeaWiFS algorithm (O'Reilley et al., 1998), which was adopted for OSMI data processing, overestimated the actual chlorophyll values. This was rather unexpected in that there were good reasons to expect that the bio-optical properties of East/Japan Sea belonged to Case 1 water and in such case, the OC2 algorithm would give unbiased estimates of actual chlorophyll a values. In November 2000, a cruise conducted bio-optical surveys in the same area. This time we added HPLC (High Performance Liquid Chromatography) method for measuring chlorophyll a concentration to the standard fluorometric method, which we hale been using during the past Fluorometric method with acidification is known to result in under/overestimation of chlorophyll values in many parts of the world oceans, while it is easier and cheaper than HPLC method. To our surprise, the comparison of HPLC chlorophyll and fluorometric chlorophyll values show that fluorometric values gave an underestimation up to 50%. This error was due to the presence of accessory pigments such as chlorophyll b. Considering this error, our precious result of May 2000(Yoo et al., 2000) might have to be reinterpreted. Calculation of reflectance at 490 and 555nm, however, indicated that this is not still enough to explain the discrepancies.