• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1265-1265
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• 2001

The organic materials included in excreta of livestock are important resources for organic manure and for improving soil quality, although there is still far from effective using. One reason for this is still unclearly standard of quality for evaluation of manure made from excreta of livestock. Therefore, the objective of this study is to develop rapid and accurate analytical method for analyzing organic compositions of manure made from excreta of livestock, and to establish quality evaluation method based on the compositions predicted by near infrared reflectance spectroscopy (NIRS). Sixteen samples of manure, each eight samples prepared from two treatments, were used in this study. The manure samples were prepared by mixing 560 kg feces of swine,60 kg sawdust with moisture content was adjusted to be 65%. The mixture was then keep under two kinds of shelter, black and clear sheets, as a treatment on the effect of sunlight. Samples were taken in every week (form week-0 to 7) during the process of manure making. Samples were analyzed to determine neutral detergent fiber (NDF), acid detergent fiber (ADF) and acid detergent lignin (ADL) by detergent methods, and organic cell wall (OCW) and fibrous content of low digestibility in OCW (Ob) by enzymatic methods. Biological oxygen demand (BOD) was analyzed by coulometric respirometer method. These compositions were carbohydrateds and lignin that were hardly digested. Spectra of samples were scanned by NIR instrument model 6500 (Pacific Scientific) and read over the range of wavelength between 400 and 2500nm. Calibration equations were developed using eight manure samples collected from black sheet shelter, while prediction was conducted to the other eight samples from clear sheet shelter. Accuracy of NTRS prediction was evaluated by correlation coefficients (r), standard error of prediction (SEP) and ration of standard deviation of reference data in prediction sample set to SEP (RPD). The r, SEP and RPD value of forage were 0.99, 0.69 and 7.6 for ADL, 0.96, 1.03 and 4.1 for NDF, 0.98, 0.60 and 4.9 for ADF, 0.92, 1.24 and 2.6 for Ob, and 0.91, 1.02 and 7.3 for BOD, respectively. The results indicated that NIRS could be used to measure the organic composition of forage used in manure samples.

• Proceedings of the KSEEG Conference
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• 2002.06a
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• pp.81-100
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• 2002

While most of regulatory communities in abroad recognize ' 'natural attenuation " to include degradation, dispersion, dilution, sorption (including precipitation and transformation), and volatilization as governing Processes, regulators prefer "degradation" because this mechanism destroys the contaminant of concern. Unfortunately, true degradation only applies to organic contaminants and short- lived radionuclides, and leaves most metals and long-lived radionuclides. The natural attenuation Processes may reduce the potential risk Posed by site contaminants in three ways: (i)contaminants could be converted to a less toxic form througy destructive processes such as biodegradation or abiotic transformations; (ii) potential exposure levels may be reduced by lowering concentrations (dilution and dispersion); and (iii) contaminant mobility and bioavailability may be reduced by sorption to geomedia. In this review, authors will focus will focul on "sorption" among the natural attenuation processes of hazardous inorganic contaminants including radionuclides. Note though that sorption and transformation processes of inorganic contaminants in the natural setting could be influenced by biotic activities but our discussion would limit only to geochemical reactions involved in the natural attenuation. All of the geochemical reactions have been studied in-depth by numerous researchers for many years to understand "retardation" process of contaminants in the geomedia. The most common approach for estimating retardation is the determination of distrubution coefficiendts ($K_{d}$) of contaminants using parametric or mechanistic models. As typocally used in fate and contaminant transport calculations such as predictive models of the natural attenuation, the $K_{d}$ is defined as the ratio of the contaminant concentration in the surrounding aqueous solution when the system is at equilibrium. Unfortunately, generic or default $K_{d}$ values can result in significant error when used to predict contaminant migration rate and to select a site remediation alternative. Thus, to input the best $K_{d}$ value in the contaminant transport model, it is essential that important geochemical processes affecting the transport should be identified and understood. Precipitation/dissolution and adsorption/desorption are considered the most important geochemical processes affecting the interaction of inorganic and radionuclide contaminants with geomedia at the near and far field, respectively. Most of contaminants to be discussed in this presentation are relatively immobile, i.e., have very high $K_{d}$ values under natural geochemical environments. Unfortunately, the obvious containment in a source area may not be good enough to qualify as monitored natural attenuation site unless owner demonstrate the efficacy if institutional controls that were put in place to protect potential receptors. In this view, natural attenuation as a remedial alternative for some of sites contaminated by hazardous-inorganic components is regulatory and public acceptance issues rather than scientific issue.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.2
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• pp.97-104
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• 2018

Recently, many studies have examined UAVs (unmanned aerial vehicles), which can replace and supplement existing surveying sensors, systems, and images. This study focused on the use of UAV images and assessed the possibility of utilization in areas where it is difficult to obtain GCPs (ground control points), such as disasters. Therefore, 3D (dimensional) pointcloud data were generated using UAV images and the absolute/relative accuracy of the generated model data using GCPs and without GCPs was assessed. The results showed the 3D shape pointcloud generated by UAV image matching was proven if the relative accuracy was set, regardless of whether GCPs were used or not; the quantitative measurement error rate was within 1%. Even if the absolute accuracy was low, the 3D shape pointcloud that had been post processed quickly was sufficient to be utilized when it is impossible to acquire GCPs or urgent analysis is required. In particular, the results can obtain quantitative measurements and meaningful data, such as the length and area, even in cases with the ground reference point surveying and post-process.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Geophysics and Geophysical Exploration
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• v.19 no.1
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• pp.11-19
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• 2016

Two representative residual static methods of traveltime decomposition and stack-power maximization are discussed in terms of application to land seismic data. For the model data with synthetic shot/receiver statics (time shift) applied and random noises added, continuities of reflection event are much improved by stack-power maximization method, resulting the derived time-shifts approximately equal to the synthetic statics. Optimal parameters (maximum allowable shift, correlation window, iteration number) for residual statics are effectively chosen with diagnostic displays of CSP (common shot point) stack and CRP (common receiver point) stack as well as CMP gather. In addition to removal of long-wavelength time shift by refraction statics, prior to residual statics, processing steps of f-k filter, predictive deconvolution and time variant spectral whitening are employed to attenuate noises and thereby to minimize the error during the correlation process. The reflectors including horizontal layer of reservoir are more clearly shown in the variable-density section through repicking the velocities after residual statics and inverse NMO correction.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.1
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• pp.58-66
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• 2010

In this paper, we have constructed high-resolution topographical map of macro-tidal Malipo beach through integration of terrestrial LiDAR measurement and MBES survey data at inter-tidal zone. To acquire the enough information of inter-tidal zone, we have done terrestrial LiDAR measurement mounted on the roof of vehicle with DGPS through go-stop-scan method at the ebb tide and MBES depth surveying with tide gauge and eye staff measurement for tide correction and MSL calculation at the high tide all together. To integrate two kinds of data, we have unified the vertical coordination standard to Incheon MSL. The mean error of overlapped inter-tidal zone is about 2~6 cm. To verify the accuracy of terrestrial LiDAR, RTK-DGPS measurement have done simultaneously and the difference of Z value RMSE is about 4~7 cm. The resolution of Malipo topographical map is 50 cm and it has constructed to DEM (Digital Elevation Model) based on GIS. Now it has used as an input topography information for the storm-surge inundation prediction models. Also it will be possible to use monitoring of beach process through the long-term periodic measurement and GIS-based 3D spatial analysis calculating the erosion and deposition considering with the artificial beach transition and coastal environmental parameters.

• Convergence Security Journal
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• v.11 no.1
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• pp.71-77
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• 2011

NCW(Network Centric- Warfare) encompasses the concept to use computer data processing and network linkage communications techniques, share information and furthermore, enhance the effectiveness of computer-operating systems. As IT(Information & Technology) have become developed in the recent years, the existing warfare system-centered conventional protocol is not use any longer. Instead, network-based NCW is being widely-available, today. Under this changing computer environment, it becomes important to establish algorithm and build the stable communication systems. Tools to identify malign node factors through Wireless Ad-hoc network cause a tremendous error to analyze and use paths of even benign node factors misreported to prove false without testing or indentifying such factors to an adequate level. These things can become an obstacle in the process of creating the optimum network distribution environment. In this regard, this thesis is designed to test and identify paths of benign node factors and then, present techniques to transmit data through the most significant open short path, with the tool of MP-SAR Protocol, security path search provider, in Ad-hoc NCW environment. Such techniques functions to identify and test unnecessary paths of node factors, and thus, such technique users can give an easy access to benign paths of node factors.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.53-64
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• 2013

In building construction project, there are numerous information or data parts across many different software applications and professional specialists. BIM (Building Information Modeling), as a medium for managing information generated during construction project, it is intended to enhance the effectiveness of construction management and reap a lot of advantages such as, automatic quantity takeoff, error-free estimation, 4D(3D+Time), 5D(4D+Cost) simulation. Nevertheless, the overall and practical effectiveness of BIM utilization is difficult to justify at this stage. While helpful, there are some limitation when BIM applied to construction management due to the differences of data processing process between BIM and work in the field, limitations of information generated from BIM object and interoperability problem among BIM application. Therefore, this paper propose a framework integrating BIM with cost-schedule information using IFC. And we construct the system prototype based on the framework and performed case study to examine the framework. The proposed framework provides the information basis for BIM based cost-schedule integration. ultimately, the framework increase the utilization of BIM and work efficiency of construction industry by supporting an understanding of information.

• Applied Chemistry for Engineering
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• v.31 no.2
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• pp.147-152
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• 2020

In this study, we dedicated to optimize the process for a reactive diluent for epoxy resin of improved chemical resistance by using cardanol, a component of natural oil of cashew nut shell liquid (CNSL). The central composite design (CCD) model of response surface methodology (RSM) was used for the optimization. The quantitative factors for CCD-RSM were the cardanol/ECH mole ratio, reaction time, and reaction temperature. The yield, epoxy equivalent, and viscosity were selected as response values. Basic experiments were performed to design the reaction surface analysis. The ranges of quantitative factors were determined as 2~4, 4~8 h, and 100~140 ℃ for the cardanol/ECH reaction mole ratio, reaction time, and reaction temperature, respectively. From the result of CCD-RSM, the optimum conditions were determined as 3.33, 6.18 h, and 120 ℃ for the cardanol/ECH reaction mole ratio, reaction time, and reaction temperature, respectively. At these conditions, the yield, epoxy equivalence, and viscosity were estimated as 100%, 429.89 g/eq., and 41.65 cP, respectively. In addition, the experimental results show that the error rate was less than 0.3%, demonstrating the validity of optimization.