• Journal of Korean Society on Water Environment
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• v.23 no.6
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• pp.863-871
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• 2007

Spectroscopic characteristics of river water from four major watersheds in the Ulsan area were measured to examine their potential for estimating water quality parameters. The total 176 river samples were collected from 44 sites of small streams within the watersheds during the year 2006. Spectroscopic characteristics investigated included protein-like fluorescence (FLF) intensity, fulvic-like fluorescence (FLF) intensity, terrestrial humic-like fluorescence (TLF) intensity, UV absorbance at 254 nm, and UV absorbance difference at 220 nm and 254 nm. Protein-like fluorescence intensity showed linear relationships with biochemical oxygen demand (BOD), chemical oxygen demand (COD), total phosphorous (TP) concentrations of the samples with the correlation of 0.784, 0.779, and 0.733, respectively. Due to the UV absorption characteristics of nitrate at 220 nm, UV absorbance difference at 220 nm and 254 nm was selected to represent total nitrogen (TN) concentration. Exclusion of some samples with PLF intensity higher than 5.0 improved the correlation between the UV absorbance difference and TN as demonstrated by the increase of the correlation coefficient from 0.392 to 0.784. Instead, for the samples with PLF intensity lower than 5.0, the highest correlation of TN was achieved with UV absorbance at 254 nm. The results suggest that PLF intensity could be used as the estimation index for BOD, COD, and TP concentration of river water, and as the primary screening index for the prediction of TN using UV absorbance difference. Some BOD-based water quality levels among the river water were statistically discriminated by the PLF intensity. Low p-values were obtained from the t-tests on the samples with the first level and the second level (p=0.0003) and the samples with the second and the third levels (p=0.0413). Our combined results demonstrated that the selected spectroscopic characteristics of river water could be utilized as a tool for on-site real-time monitoring and/or the primary estimation of water quality.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.29-35
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• 2007

This study was designed to investigate the feasibility to utilize the electromyogram (EMG) for estimating the muscle torque. The muscle torque estimation plays an important role in functional electrical stimulation because electrical stimulation causes muscles to fatigue much faster than voluntary contraction, and the stimulation intensity should then be modified to keep the muscle torque within the desired range. We employed the neural network method which was trained using the major EMG parameters and the corresponding knee extensor torque measured and extracted during isometric contractions. The experimental results suggested that (1) our neural network algorithm and protocol was feasible to be adopted in a real-time feedback control of the stimulation intensity, (2) the training data needed to cover the entire range of the measured value, (3) different amplitudes and frequencies made little difference to the estimation quality, and (4) a single input to the neural network led to a better estimation rather than a combination of two or three. Since this study was done under a limited contraction condition, the results need more experiments under many different contraction conditions, such as during walking, for justification.

• Journal of Environmental Science International
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• v.19 no.7
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• pp.907-915
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• 2010

Agriculture nonpoint pollution source is a significant contributor to water quality degradation. To establish effective water quality control policy, environpolitics establishment person must be able to estimate nonpoint source loads to lakes and streams. To meet this need for orchard area, we investigated a real rainfall runoff phenomena about it. We developed nonpoint source runoff estimation models for vineyard area that has lots of fertilizer, compost specially between agricultural areas. Data used in nonpoint source estimation model gained from real measuring runoff loads and it surveyed for two years(2008-2009 year) about vineyard. Nonpoint source runoff loads estimation models were composed of using independent variables(rainfall, storm duration time(SDT), antecedent dry weather period(ADWP), total runoff depth(TRD), average storm intensity(ASI), average runoff intensity(ARI)). Rainfall, total runoff depth and average runoff intensity among six independent variables were specially high related to nonpoint source runoff loads such as BOD, COD, TN, TP, TOC and SS. The best regression model to predict nonpoint source runoff load was Model 6 and regression factor of all water quality items except for was $R^2=0.85$.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.47-54
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• 2001

This paper considers the parameter estimation problem of the failure intensity function and maintenance effect in a repairable system. We propose estimation procedures for repairable systems on which preventive maintenance is performed. The failure process is modeled by a proportional age reduction model [Brown, Mahoney and Sivazlian(1983)] which is useful to model the imperfect effect of preventive maintenance. When failure and maintenance (preventive) times are given, the maximum likelihood method is used to estimate the maintenance effect and the parameters of intensity function, simultaneously We obtain the maximum likelihood estimators using a genetic algorithm. A numerical example is also presented.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1997.04a
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• pp.21-26
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• 1997

For 262 locations throughout the southern part of Korean peninsula, intensities of 13 December 1996 Yeongweol earthquake are estimated to make an isoseismal map and investigate attenuation properties in the southern part of Korea. Due to the inherent uncertainties in the estimation of intensities, obtained intensity map show quite scattered pattern of intensity distribution. Estimated intensities range from III to possibly Ⅷ. In case of intensity larger than Ⅵ, considerable damages such as fracturing of walls are reported one of the most significant feature of the intensity map is, considering its magnitude 4.7 reported by KMA, the felt area is appeared to be unusually large covering most of the Korean peninsula except Cheju island. This result indicates ether the magnitude is underestimated or the focus of this earthquake is much deeper. Assuming shallow(less than 10km) intraplate earthquake, we obtained average magnitude 5.6 by using the area encircled by isoseismal contour lines from intensity IV to intensity Ⅶ. This ambiguity can be clarified if more reliable focal depth is estimated by using teleseismic earthquake records in the future.

• ETRI Journal
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• v.38 no.5
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• pp.1019-1029
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• 2016

The probability hypothesis density (PHD) filter is an effective means to track multiple targets in that it avoids explicit data associations between the measurements and targets. However, the target birth intensity as a prior is assumed to be known before tracking in a traditional target-tracking algorithm; otherwise, the performance of a conventional PHD filter will decline sharply. Aiming at this problem, a novel target birth intensity scheme and an improved measurement-driven scheme are incorporated into the PHD filter. The target birth intensity estimation scheme, composed of both PHD pre-filter technology and a target velocity extent method, is introduced to recursively estimate the target birth intensity by using the latest measurements at each time step. Second, based on the improved measurement-driven scheme, the measurement set at each time step is divided into the survival target measurement set, birth target measurement set, and clutter set, and meanwhile, the survival and birth target measurement sets are used to update the survival and birth targets, respectively. Lastly, a Gaussian mixture implementation of the PHD filter is presented under a linear Gaussian model assumption. The results of numerical experiments demonstrate that the proposed approach can achieve a better performance in tracking systems with an unknown newborn target intensity.

• Earthquakes and Structures
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• v.16 no.2
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• pp.197-208
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• 2019

The objective of this study is to propose new seismic intensity parameters based on the Hilbert spectrum and to associate them with the seismic damage potential. In recent years the assessment of even more seismic features derived from the seismic acceleration time-histories was associated with the structural damage. For a better insight into the complex seismic acceleration time-history, Hilbert-Huang Transform (HHT) analysis is utilized for its processing, and the Hilbert spectrum is obtained. New proposed seismic intensity parameters based on the Hilbert spectrum are derived. The aim is to achieve a significant estimation of the seismic damage potential on structures from the proposed new intensity parameters confirmed by statistical methods. Park-Ang overall structural damage index is used to describe the postseismic damage status of structures. Thus, a set of recorded seismic accelerograms from all over the word is applied on a reinforced concrete frame structure, and the Park-Ang indices through nonlinear dynamic analysis are provided and considered subsequently as reference numerical values. Conventional seismic parameters, with well-known seismic structural damage interrelation, are evaluated for the same set of excitations. Statistical procedures, namely correlation study and multilinear regression analysis, are applied on the set of the conventional parameters and the set of proposed new parameters separately, to confirm their interrelation with the seismic structural damage. The regression models are used for the evaluation of the structural damage indices for every set of parameters, respectively. The predicted numerical values of the structural damage indices evaluated from the two sets of seismic intensity parameters are inter-compared with the reference values. The numerical results confirm the ability of the proposed Hilbert spectrum based new seismic intensity parameters to approximate the postseismic structural damage with a smaller Standard Error of Estimation than this accomplished of the conventional ones.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1839-1845
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• 2016

Detecting remote targets is important to active protection system (APS) or infrared search and track (IRST) applications. In normal situation, the well-known constant false alarm rate (CFAR) detector works properly. However, decoys in APS or closely spaced targets in IRST degrade the detection capability by increasing background noise level in the CFAR detector. This paper presents a context aware CFAR detector by the intensity sorting and selection of background region to reduce the effect of neighboring targets that lead to incorrect estimation of background statistics. The existence of neighboring targets can be recognized by intensity sorting where neighboring targets usually show highest ranks. The proposed background statistics (mean, standard deviation) estimation method from median local pixels can be aware of the background context and reduce the effects of the neighboring targets, which increase the signal-to-clutter ratio. The experimental results on the synthetic APS sequence, real adjacent target sequence, and remote pedestrian sequence validated that the proposed method produced an enhanced detection rate with the same false alarm rate compared with the hysteresis-CFAR (H-CFAR) detection.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.1053-1056
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• 2007

The acoustical performance of noise reducing devices installed on the top of a noise barrier were tested by small-scale outdoor tests. Noise measurements before and after installation of the devices were carried out using sound intensity methods. It is well known that the sound intensity method can specify the strength and directivity of sound, and it is convenient to consider the feature of sound around a noise barrier. The noise reduction effect of each edge device was evaluated using the difference between the input and output sound power levels calculated from sound intensities. It was investigated that each device had different efficiency in the shadow zone, while there was no significant difference between edge devices in the illuminated zone.

• Korean Journal of Remote Sensing
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• v.23 no.1
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• pp.33-42
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• 2007

In this paper, an iterative MAP approach using a Bayesian model based on the lognormal distribution for image intensity and a GRF for image texture is proposed for despeckling the SAR images that are corrupted by multiplicative speckle noise. When the image intensity is logarithmically transformed, the speckle noise is approximately Gaussian additive noise, and it tends to a normal probability much faster than the intensity distribution. MRFs have been used to model spatially correlated and signal-dependent phenomena for SAR speckled images. The MRF is incorporated into digital image analysis by viewing pixel types as slates of molecules in a lattice-like physical system defined on a GRF Because of the MRF-SRF equivalence, the assignment of an energy function to the physical system determines its Gibbs measure, which is used to model molecular interactions. The proposed Point-Jacobian Iterative MAP estimation method was first evaluated using simulation data generated by the Monte Carlo method. The methodology was then applied to data acquired by the ESA's ERS satellite on Nonsan area of Korean Peninsula. In the extensive experiments of this study, The proposed method demonstrated the capability to relax speckle noise and estimate noise-free intensity.