• Title/Summary/Keyword: Process-error model

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Data issue and Improvement Direction for Marine Spatial Planning (해양공간계획 지원을 위한 정보 현안 및 개선 방향 연구)

  • CHANG, Min-Chol;PARK, Byung-Moon;CHOI, Yun-Soo;CHOI, Hee-Jung;KIM, Tae-Hoon;LEE, Bang-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.21 no.4
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    • pp.175-190
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    • 2018
  • Recently, policy of the marine advanced countries were switched from the preemption using ocean to post-project development. In this study, we suggest improvement and the pending issues when are deducted to the database of the marine spatial information is constructed over the GIS system for the Korean Marine Spatial Planning (KMSP). More than 250 spatial information in the seas of Korea were processed in order of data collection, GIS transformation, data analysis and processing, data grouping, and space mapping. It's process had some problem occurred to error of coordinate system, digitizing process for lack of the spatial information, performed by overlapping for the original marine spatial information, and so on. Moreover, solution is needed to data processing methods excluding personal information which is necessary when produce the spatial data for analysis of the used marine status and minimized method for different between the spatial information based GIS system and the based real information. Therefore, collection and securing system of lacking marine spatial information is enhanced for marine spatial planning. it is necessary to link and expand marine fisheries survey system. It is needed to the marine spatial planning. The marine spatial planning is required to the evaluation index of marine spatial and detailed marine spatial map. In addition, Marine spatial planning is needed to standard guideline and system of quality management. This standard guideline generate to phase for production, processing, analysis, and utilization. Also, the quality management system improve for the information quality of marine spatial information. Finally, we suggest necessity need for the depths study which is considered as opening extension of the marine spatial information and deduction on application model.

Near Infrared Spectroscopy for Diagnosis: Influence of Mammary Gland Inflammation on Cow´s Milk Composition Measurement

  • Roumiana Tsenkova;Stefka Atanassova;Kiyohiko Toyoda
    • Near Infrared Analysis
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    • v.2 no.1
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    • pp.59-66
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    • 2001
  • Nowadays, medical diagnostics is efficiently supported by clinical chemistry and near infrared spectroscopy is becoming a new dimension, which has shown high potential to provide valuable information for diagnosis. The investigation was carried out to study the influence of mammary gland inflammation, called mastitis, on cow´s milk spectra and milk composition measured by near infrared spectroscopy (NIRS). Milk somatic cell counts (SCC) in milk were used as a measure of mammary gland inflammation. Naturally occurred variations with milk composition within lactation and in the process of milking were included in the experimental design of this study. Time series of unhomogenized, raw milk spectral data were collected from 3 cow along morning and evening milking, for 5 consecutive months, within their second lactation. In the time of the trial, the investigated cows had periods with mammary gland inflammation. Transmittance spectra of 258 milk samples were obtained by NIRSystem 6500 spectrophotometer in 1100-2400 nm region. Calibration equations for the examined milk components were developed by PLS regression using 3 different sets of samples: samples with low somatic cell count (SCC), samples with high SCC and combined data set. The NIR calibration and prediction of individual cow´s milk fat, protein, and lactose were highly influenced by the presence of mil samples from animals with mammary gland inflammation in the data set. The best accuracy of prediction (i.e. the lower SEP and the higher correlation coefficient) for fat, protein and lactose was obtained for equations, developed when using only “healthy” samples, with low SCC. The standard error of prediction increased and correlation coefficient decreased significantly when equations for low SCC milk were used to predict examined components in “mastitis” samples with high SCC, and vice versa. Combined data set that included samples from healthy and mastitis animals could be used to build up regression models for screening. Further use of separate model for healthy samples improved milk composition measurement. Regression vectors for NIR mild protein measurement obtained for “healthy” and “mastitic” group were compared and revealed differences in 1390-1450 nm, 1500-1740 nm and 1900-2200 nm regions and thus illustrated post-secretory breakdown of milk proteins by hydrolytic enzymes that occurred with mastitis. For the first time it has been found that monitoring the spectral differences in water bands at 1440 nm and 1912 nm could provide valuable information for inflammation diagnosis.

The Case Study on Application of 3 Dimensional Modeling Method with Geophysical Data (물리탐사 자료에 대한 3차원 지반 모델링 적용 사례 연구)

  • Heo, Seung;Park, Joon-Young;Do, Jung-Lok;Yoo, In-Kol
    • Geophysics and Geophysical Exploration
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    • v.11 no.3
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    • pp.221-229
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    • 2008
  • The three dimensional model method is widely applied in resource development for feasibility study, mine design, excavation planning and process management by constructing the database of various data in 3 dimensional space. Most of geophysical surveys for the purpose of engineering and resource development are performed in 2 dimensional line survey due to the restriction of the field situation, technical or economical situation and so on. The acquired geophysical data are used as the input for the 2 dimensional inversion under the 2 dimensional assumption. But the geophysical data are affected by 3 dimensional space. Therefore in order to reduce the error caused by 2 dimensional assumption, the 2 dimensional inversion result must be interpreted considering the additional information such as 3 dimensional topography, geological structure, borehole survey etc. The applicability and usability of 3 dimensional modeling method are studied by reviewing the case study to the geophysical data acquired in field of engineering and resource development.

Sewer overflow simulation evaluation of urban runoff model according to detailed terrain scale (상세지형스케일에 따른 도시유출모형의 관거월류 모의성능평가)

  • Tak, Yong Hun;Kim, Young Do;Kang, Boosik;Park, Mun Hyun
    • Journal of Korea Water Resources Association
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    • v.49 no.6
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    • pp.519-528
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    • 2016
  • Frequently torrential rain is occurred by climate change and urbanization. Urban is formed with road, residential and underground area. Without detailed topographic flooded analysis consideration can take a result which are wrong flooded depth and flooded area. Especially, flood analysis error of population and assets in dense downtown is causing a big problem for establishments and disaster response of flood measures. It can lead to casualties and property damage. Urban flood analysis is divided into sewer flow analysis and surface inundation analysis. Accuracy is very important point of these analysis. In this study, to confirm the effects of the elevation data precision in the process of flooded analysis were studied using 10m DEM, LiDAR data and 1:1,000 digital map. Study area is Dorim-stream basin in the Darim drainage basin, Sinrim 3 drainage basin, Sinrim 4 drainage basin. Flooding simulation through 2010's heavy rain by using XP-SWMM. Result, from 10m DEM, shows wrong flood depth which is more than 1m. In particular, some of the overflow manhole is not seen occurrence. Accordingly, detailed surface data is very important factor and it should be very careful when using the 10m DEM.

Experiments of Individual Tree and Crown Width Extraction by Band Combination Using Monthly Drone Images (월별 드론 영상을 이용한 밴드 조합에 따른 수목 개체 및 수관폭 추출 실험)

  • Lim, Ye Seul;Eo, Yang Dam;Jeon, Min Cheol;Lee, Mi Hee;Pyeon, Mu Wook
    • Journal of Korean Society for Geospatial Information Science
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    • v.24 no.4
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    • pp.67-74
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    • 2016
  • Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

Development of an Artificial Neural Expert System for Rational Determination of Lateral Earth Pressure Coefficient (합리적인 측압계수 결정을 위한 인공신경 전문가 시스템의 개발)

  • 문상호;문현구
    • Journal of the Korean Geotechnical Society
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    • v.15 no.1
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    • pp.99-112
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    • 1999
  • By using 92 values of lateral earth pressure coefficient(K) measured in Korea, the tendency of K with varying depth is analyzed and compared with the range of K defined by Hoek and Brown. The horizontal stress is generally larger than the vertical stress in Korea : About 84 % of K values are above 1. In this study, the theory of elasto-plasticity is applied to analyze the variation of K values, and the results are compared with those of numerical analysis. This reveals that the erosion, sedimentation and weathering of earth crust are important factors in the determination of K values. Surface erosion, large lateral pressure and good rock mass increase the K values, but sedimentation decreases the K values. This study enable us to analyze the effects of geological processes on the K values, especially at shallow depth where underground excavation takes place. A neural network expert system using multi-layer back-propagation algorithm is developed to predict the K values. The neural network model has a correlation coefficient above 0.996 when it is compared with measured data. The comparison with 9 measured data which are not included in the back-propagation learning has shown an average inference error of 20% and the correlation coefficient above 0.95. The expert system developed in this study can be used for reliable determination of K values.

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Target Identification for Metabolic Engineering: Incorporation of Metabolome and Transcriptome Strategies to Better Understand Metabolic Fluxes

  • Lindley, Nic
    • Proceedings of the Korean Society for Applied Microbiology Conference
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    • 2004.06a
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    • pp.60-61
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    • 2004
  • Metabolic engineering is now a well established discipline, used extensively to determine and execute rational strategies of strain development to improve the performance of micro-organisms employed in industrial fermentations. The basic principle of this approach is that performance of the microbial catalyst should be adequately characterised metabolically so as to clearlyidentify the metabolic network constraints, thereby identifying the most probable targets for genetic engineering and the extent to which improvements can be realistically achieved. In order to harness correctly this potential, it is clear that the physiological analysis of each strain studied needs to be undertaken under conditions as close as possible to the physico-chemical environment in which the strain evolves within the full-scale process. Furthermore, this analysis needs to be undertaken throughoutthe entire fermentation so as to take into account the changing environment in an essentially dynamic situation in which metabolic stress is accentuated by the microbial activity itself, leading to increasingly important stress response at a metabolic level. All too often these industrial fermentation constraints are overlooked, leading to identification of targets whose validity within the industrial context is at best limited. Thus the conceptual error is linked to experimental design rather than inadequate methodology. New tools are becoming available which open up new possibilities in metabolic engineering and the characterisation of complex metabolic networks. Traditionally metabolic analysis was targeted towards pre-identified genes and their corresponding enzymatic activities within pre-selected metabolic pathways. Those pathways not included at the onset were intrinsically removed from the network giving a fundamentally localised vision of pathway functionality. New tools from genome research extend this reductive approach so as to include the global characteristics of a given biological model which can now be seen as an integrated functional unit rather than a specific sub-group of biochemical reactions, thereby facilitating the resolution of complexnetworks whose exact composition cannot be estimated at the onset. This global overview of whole cell physiology enables new targets to be identified which would classically not have been suspected previously. Of course, as with all powerful analytical tools, post-genomic technology must be used carefully so as to avoid expensive errors. This is not always the case and the data obtained need to be examined carefully to avoid embarking on the study of artefacts due to poor understanding of cell biology. These basic developments and the underlying concepts will be illustrated with examples from the author's laboratory concerning the industrial production of commodity chemicals using a number of industrially important bacteria. The different levels of possibleinvestigation and the extent to which the data can be extrapolated will be highlighted together with the extent to which realistic yield targets can be attained. Genetic engineering strategies and the performance of the resulting strains will be examined within the context of the prevailing experimental conditions encountered in the industrial fermentor. Examples used will include the production of amino acids, vitamins and polysaccharides. In each case metabolic constraints can be identified and the extent to which performance can be enhanced predicted

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Prediction of Chemical Organic Composition of Manure by Near Infrared Reflectance Spectroscopy

  • Amari, Masahiro;Fukumoto, Yasuyuki;Takada, Ryozo
    • 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.

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NATURAL ATTENUATION OF HAZARDOUS INORGANIC COMPONENTS: GEOCHEMISTRY PROSPECTIVE (유해 무기질의 자연정화 : 지화학적 고찰)

  • Lee, Suk-Young;Lee, Chae-Young;Yun, Jun-Ki
    • 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.

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A Study on Utilization 3D Shape Pointcloud without GCPs using UAV images (UAV 영상을 이용한 무기준점 3D 형상 점군데이터 활용 연구)

  • Kim, Min-Chul;Yoon, Hyuk-Jin
    • 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.