• Journal of Advanced Navigation Technology
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• v.17 no.5
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• pp.506-515
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• 2013

In cognitive radio networks, several research works typically address the framework which consists of a spectrum sensing period and a data transmission period. When the frame period is short, there is the problem that the throughput of secondary users decrease. In this paper, aggregated data slot structure is considered to increase the throughput of secondary users. Chapman-Kolmogorov equation is used for the modeling of the transmission probability of primary users and formulation of an optimization problem to maximize the throughput of secondary users. Solution of the optimization problem results in the optimal spectrum sensing time, the length of data slot and the number of data slots governed by a spectrum sensing.

• Proceedings of the KSRS Conference
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• v.1
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• pp.290-293
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• 2006

COMS (Communication, Ocean and Meteorological Satellite) shall be operated with two remote sensing payloads, MI (Meteorological Imager) and GOCI (Geostationary Ocean Color Imager). Since both payloads have rotating mechanisms, the dynamic coupling between two payloads is very important considering the pointing stability during GOCI operation. In addition, COMS adopts a single solar wing to improve the image quality, which leads to the unbalanced solar pressure torque in COMS. As a result, the off-loading of the wheel momentum needs to be performed regularly (2 times per day). Since the frequent off-loading could affect MI/GOCI imaging performance, another suboptimal off-loading time needs to be considered to meet the AOCS design requirements of COMS while having margin enough in the number of thruster actuations. In this paper, preliminary analysis results on the pointing stability and the wheel off-loading time selection with respect to MI/GOCI operations are presented.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.10-12
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• 2003

This study was to monitor changes of leaf area index (LAI) and normalized difference vegetation index (NDVI), calculated from ground-based remotely sensed high resolution reflectance spectra, during rice (Oryza sativa L. cv. TNG 67) growth so as to determine their relationships and the optimum time period to use these parameters for yield prediction. Field experiments were conducted at the experimental farm of TARI to obtain various scales of grain yield and values of LAI and NDVI in the first and the second cropping seasons of 2001-2002. It was found that LAI and NDVI can be mutually estimated through an exponential relationship, and hence plant growth information and spectral remote sensing data become complementary counterparts through this linkage. Correlation between yield and LAI was best fitted to a nonlinear function since about 7 weeks after transplanting (WAT). The accumulated and the mean values of LAI from 15 days before heading (DBH) to 15 days after heading (DAH) were the optimum time period to predict rice yield for First Crops, while values calculated from 15 DBH to 10 DAH were the optimal timing for Second Crops.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1255-1261
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• 2016

Recently, the energy harvesting technology in which energy is collected from the wireless signal which is transmitted by mobile communication devices, has been considered as a novel way to improve the life time of wireless sensors by mitigating the lack of power supply problem. In this paper, we consider the optimal sensing time and power allocation problem for cognitive radio systems, where the energy efficiency of secondary user is maximized while the constraint are satisfied, using the optimization technique. Based on the derived optimal solutions, we also have proposed an iterative resource allocation algorithm in which the optimal power and sensing time allocation can be found without excessive computations. The simulation results confirm that the proposed scheme achieves the optimal performance and it outperforms the conventional resource allocation schemes in terms of energy efficiency while the constraints are guaranteed to be satisfied.

• Nano
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• v.13 no.10
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• pp.1850115.1-1850115.10
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• 2018

A novel sensor material of Au nanoparticles (NPs) functionalized 1D ${\alpha}-MoO_3$ nanobelts (NBs) was fabricated by a facile lysine-assisted approach. The obtained $Au/{\alpha}-MoO_3$ product was characterized by means of X-ray diffraction (XRD), scanning electron microscope (SEM), transmission electron microscope (TEM) and energy dispersive X-ray (EDX), and X-ray photoelectron spectra (XPS). Then, in order to investigate the gas sensing performances of our samples, a comparative gas sensing study was carried out on both the ${\alpha}-MoO_3$ NBs before and after Au NPs decoration by using ethanol vapor as the molecular probe. The results turned out that, after the functionalization of Au NPs, the sensor exhibited improved gas-sensing characteristics than the pure ${\alpha}-MoO_3$, such as response and recovery time, optimal operating temperature (OT) and excellent selectivity. Take for example 200 ppm of ethanol, the response/recovery times were 34 s/43 s and 5.7 s/10.5 s, respectively, while the optimal operating temperature (OT) was lower to $200^{\circ}C$ rather than $250^{\circ}C$. Besides, the functionalized sensor showed a higher response to ethanol at $200^{\circ}C$, and response was 1.6 times higher than the pure $MoO_3$. The mechanism of such improved sensing properties was interpreted, which might be attributed to the spillover effect of Au NPs and the electronic metal-support interaction.

• Korean Journal of Remote Sensing
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• v.7 no.1
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• pp.45-67
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• 1991

An overview is given on stochastic techniques with which remotely sensed data may be used together with ground measurements for purposes of state estimation and prediction. They can explicitly account for spatiotemporal differences in measurement characteristics between ground measurements and remotely sensed data, and are suitable for highly variant space or space-time processes, such as atmosperic processes, which may be viewed as (containing) a random process. For state estimation of static ststems, optimal linear estimation is described. As alternatives, various co-kriging estimation techniques are also described, including simple, ordinary, universal, lognormal, disjunctive, indicator, and Bayesian extersion to simple and lognormal. For illustrative purposes, very simple examples of optimal linear estimation and simple co-kriging are given. For state estimation and prediction of dynamic system, distributed-parameter kalman filter is described. Issues concerning actual implemention are given, and with application potential are described.

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.645-652
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• 2010

The performance of the payload Electro-Optical System (EOS) in satellite system is affected by various factors, such as optics design, camera electronics design, and the characteristics of the CCD (Charge Coupled Device) used, etc. Of these factors, the camera electronics design is somewhat unique in that its operational parameters can be adjusted even after the satellite launch. In this paper, the effect of video gain on the non-uniformity correction performance is addressed. And a new optimal non-uniformity correction scheme is proposed and analyzed using the data from real camera electronics unit based on a TDI (Time Delayed Integration) type of CCD. The test results show that the performance of the conventional non-uniformity correction scheme is affected significantly when the video gain is added. On the other hand, in our proposed scheme, the performance is not dependent on the video gain. The insensitivity of the non-uniformity performance on the video-gain is mainly due to the fact that the correction is performed after the dark signal is subtracted from system response.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• Bulletin of the Korean Chemical Society
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• v.34 no.11
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• pp.3307-3311
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• 2013

A new fiber optical sensor was developed for the determination of 2,4-dichlorophenol (DCP). The sensor was based on DCP oxidation by oxygen with the catalysis of iron(III) tetrasulfophthalocyanine (Fe(III)PcTs). The optical oxygen sensing film with $Ru(bpy)_3Cl_2$ as the fluorescence indicator was used to determine the consumption of oxygen in solution. A lock-in amplifier was used for detecting the lifetime of the oxygen sensing film by measuring the phase delay change of the sensor head. The different variables affecting the sensor performance were evaluated and optimized. Under the optimal conditions (i.e. pH 6.0, $25^{\circ}C$, Fe(III)PcTs concentration of 0.62 mg/mL), the linear detection range and response time of the sensor are $1.0{\times}10^{-6}-9.0{\times}10^{-6}$ mol/L and 250 s, respectively. The sensor displays high selectivity, good repeatability and stability, and can be used as an effective tool in analyzing DCP concentration in practical samples.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1400-1402
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• 2003

The objective of this paper is to determine the suitable spectral bands for monitoring growth status change during a long period. The long-term ground-level reflectance spectra as well as LAI and biomass were obtained in xiaotangshan area, Beijing, 2001. The narrow-band NDVI type spectral indices by all possible two bands were calculated their correlation coefficients R$^2$ with biomass and LAI. The best NDVIs must have higher R$^2$ with both biomass and LAI. The reasonable band centers and band widths were determined by a systematically increasing bandwidth centered over a wavelength. In addition, the first 19 bands of MODIS were simulated and investigated. Each developed spectral indices was then validated by the biomass and LAI time series using the generalized vector angle. It turned out that six new NDVI type indices within 750-1400nm were developed. NDVI(811_10,957_10) and NDVI(962_10,802_10) performed best. No satisfactory conventional NDVI formed by red and NIR bands were found effective. MODIS_NDVI(band19, band17) and MODIS_NDVI(band19, band2) were much better than MODIS_NDVI(band2,band1) for growth monitoring.