• Title/Summary/Keyword: quantitative models

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A Review on the Photochemical Oxidant Modeling as Applied to Air Quality Studies in Complex Terrain

  • Lee Hwa-Woon;Kim Yoo-Keun;Won Gyeong-Mee;Park Jong-Kil
    • Environmental Sciences Bulletin of The Korean Environmental Sciences Society
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    • v.1 no.1
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    • pp.19-33
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    • 1997
  • The high oxidants, which occur the daily maximum concentrations in the afternoon, are transported into the other region via long range transport mechanisms or trapped within the shallow mixing boundary layer and then removed physically (deposition, transport by mountain wind, etc.) and chemically (reaction with local sources). Therefore, modeling formation of photochemical oxidants requires a complex description of both chemical and meteorological processes. In this study, as a part of air quality studies, we reviewed various aspects of photochemical modeling on the basis of currently available literature. The result of the review shows that the model is based on a set of coupled continuity equations describing advection, diffusion, transport, deposition, chemistry, emission. Also photochemical oxidant models require a large amount of input data concerned with all aspects of the ozone life cycle. First, emission inventories of hydrocarbon and nitrogen oxides, with appropriate spatial and temporal resolution. Second, chemical and photochemical data allowing the quantitative description of the formation of ozone and other photochemically-generated secondary pollutants. Third, dry deposition mechanisms particularly for ozone, PAN and hydrogen peroxide to account for their removal by absorption on the ground, crops, natural vegetation, man-made and water surfaces. Finally, meteorological data describing the transport of primary pollutants away from their sources and of secondary pollutants towards the sensitive receptors where environmental damage may occur. In order to improve our present study, shortcomings and limitation of existing models are pointed out and verification process through observation is emphasized.

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Comparative Molecular Field Analysis (CoMFA) and Comparative Molecular Similarity Index Analysis (CoMSIA) Study of Mutagen X

  • Bang, Soo-Jin;Cho, Seung-Joo
    • Bulletin of the Korean Chemical Society
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    • v.25 no.10
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    • pp.1525-1530
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    • 2004
  • Mutagen X (MX) exists in our drinking water as the bi-products of chlorine disinfection. Being one of the most potent mutagen, it attracted much attention from many researchers. MX and its analogs are synthesized and modeled by quantitative structure activity relationship (QSAR) methods. As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. We tried to collect all the data available from the literature. With both CoMFA and CoMSIA various combinations of physiochemical parameters were systematically studied to produce reasonable 3-dimensional models. The best model for CoMFA gave $q^2$ = 0.90 and $r^2$ = 0.97, while for CoMSIA $q^2$ = 0.85 and $r^2$ = 0.94. So the models seem to be reasonable. Unlike previous result of CoMFA, in our case steric parameter alone gave the best statistics. Although the steric contribution was found to be the most important in both CoMFA and CoMSIA, steric parameter along with electrostatic parameter produced slightly better model in CoMSIA. Overall, steric contribution is clearly the most important single factor. However, when we compare chlorine and bromine substitution, chlorine substitution can be more mutagenic. This indicates that other factors such as electrostatic effect also influence the mutagenicity. From the contour maps, steric contribution seems to be focused on rather small area near C6 substituent of the furanone ring, rather than C3 substituent. Therefore the locality of steric contribution can play a significant role in mutagenicity.

Econometric Study on Forecasting Demand Response in Smart Grid (스마트그리드 수요반응 추정을 위한 계량경제학적 방법에 관한 연구)

  • Kang, Dong Joo;Park, Sunju
    • KIPS Transactions on Computer and Communication Systems
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    • v.1 no.3
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    • pp.133-142
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    • 2012
  • Cournot model is one of representative models among many game theoretic approaches available for analyzing competitive market models. Recent years have witnessed various kinds of attempts to model competitive electricity markets using the Cournot model. Cournot model is appropriate for oligopoly market which is one characteristic of electric power industry requiring huge amount of capital investment. When we use Cournot model for the application to electricity market, it is prerequisite to assume the downward sloping demand curve in the right direction. Generators in oligopoly market could try to maximize their profit by exercising the market power like physical or economic withholding. However advanced electricity markets also have demand side bidding which makes it possible for the demand to respond to the high market price by reducing their consumption. Considering this kind of demand reaction, Generators couldn't abuse their market power. Instead, they try to find out an equilibrium point which is optimal for both sides, generators and demand. This paper suggest a quantitative analysis between market variables based on econometrics for estimating demand responses in smart grid environment.

Image Segmentation of Lung Parenchyma using Improved Deformable Model on Chest Computed Tomography (개선된 가변형 능동모델을 이용한 흉부 컴퓨터단층영상에서 폐 실질의 분할)

  • Kim, Chang-Soo;Choi, Seok-Yoon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.13 no.10
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    • pp.2163-2170
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    • 2009
  • We present an automated, energy minimized-based method for Lung parenchyma segmenting Chest Computed Tomography(CT) datasets. Deformable model is used for energy minimized segmentation. Quantitative knowledge including expected volume, shape of Chest CT provides more feature constrain to diagnosis or surgery operation planning. Segmentation subdivides an lung image into its consistent regions or objects. Depends on energy-minimizing, the level detail image of subdivision is carried. Segmentation should stop when the objects or region of interest in an application have been detected. The deformable model that has attracted the most attention to date is popularly known as snakes. Snakes or deformable contour models represent a special case of the general multidimensional deformable model theory. This is used extensively in computer vision and image processing applications, particularly to locate object boundaries, in the mean time a new type of external force for deformable models, called gradient vector flow(GVF) was introduced by Xu. Our proposed algorithm of deformable model is new external energy of GVF for exact segmentation. In this paper, Clinical material for experiments shows better results of proposal algorithm in Lung parenchyma segmentation on Chest CT.

Estimating Carbon Emissions due to Freeway Incidents by Using Macroscopic Traffic Flow Models (거시적 교통류모형을 이용한 고속도로 돌발상황에 따른 탄소배출량 산정연구)

  • Son, Young Tae;Han, Kyu Jong
    • International Journal of Highway Engineering
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    • v.18 no.1
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    • pp.119-129
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    • 2016
  • PURPOSES : The purpose of this study is to develop a methodology for estimating additional carbon emissions due to freeway incidents. METHODS : As our country grows, our highway policy has mainly neglected the environmental and social sectors. However, with the formation of a national green growth keynote and an increase in the number of people interested in environmental and social issues, problems related to social issues, such as traffic accidents and congestion, and environmental issues, such as the impact of air pollution caused by exhaust gases that are emitted from highway vehicles, are beginning to be discussed. Accordingly, studies have been conducted on a variety of environmental aspects in the field of road transport, and for the quantitative calculation of greenhouse gas emissions, using various methods. However, in order to observe the effects of carbon emissions, microscopic simulations must use many difficult variables such as cost, analysis time, and ease of analysis process. In this study, additional greenhouse gas emissions that occur because of highway traffic accidents were classified by type (incident handling time, number of lanes blocked, freeway level of service), and the annual additional emissions based on incidents were calculated. According to the results, congestion length and emissions tend to increase with an increase in incident clearance time, number of occupied lanes, and worsening level of service. Using this data, we analyzed accident data on the Gyeong-bu Expressway (Yang-Jae IC - Osan IC) for a year. RESULTS : Additional greenhouse gas emissions that occur because of highway traffic accidents were classified by type (incident handling time, number of lanes blocked, freeway level of service) and annual additional emissions caused by accidents were calculated. CONCLUSIONS : In this study, a methodology for estimating carbon emissions due to freeway incidents was developed that incorporates macroscopic flow models. The results of the study are organized in the form of a look-Up table that calculates carbon emissions rather easily.

Pratical Offloading Methods and Cost Models for Mobile Cloud Computing (모바일 클라우드 컴퓨팅을 위한 실용적인 오프로딩 기법 및 비용 모델)

  • Park, Min Gyun;Zhe, Piao Zhen;La, Hyun Jung;Kim, Soo Dong
    • Journal of Internet Computing and Services
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    • v.14 no.2
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    • pp.73-85
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    • 2013
  • As a way of augmenting constrained resources of mobile devices such as CPU and memory, many works on mobile cloud computing (MCC), where mobile devices utilize remote resources of cloud services or PCs, /have been proposed. A typical approach to resolving resource problems of mobile nodes in MCC is to offload functional components to other resource-rich nodes. However, most of the current woks do not consider a characteristic of dynamically changed MCC environment and propose offloading mechanisms in a conceptual level. In this paper, in order to ensure performance of highly complex mobile applications, we propose four different types of offloading mechanisms which can be applied to diverse situations of MCC. And, the proposed offloading mechanisms are practically designed so that they can be implemented with current technologies. Moreover, we define cost models to derive the most sutilable situation of applying each offloading mechanism and prove the performance enhancement through offloadings in a quantitative manner.

Risk Assessment and Contingency Prediction considering Work Characteristics for Modular Plant Construction Projects (모듈러 플랜트의 업무특성을 고려한 위험 평가 및 예비비 예측)

  • Kang, Hyunwook;Kim, Jongwook;Kim, Yongsu
    • Korean Journal of Construction Engineering and Management
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    • v.19 no.5
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    • pp.81-89
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    • 2018
  • The purpose of this study is to assess the risk and predict the contingency for modular plant construction projects. Considering the work characteristics of the modular plant, The adapted research method is that suggest models for assessment impact of risk and predict the contingency considering risk. Based on the proposed models, It is selected one modular plant construction project and assessment impact of risk factors and predicted the contingency. The results of this study are as follows: Assessment the probability of occurrence of risk factors and intensity of impact, and extract 15 important risk factors. These are classified as Engineering, Procurement, Fabrication, Transportation, Construction phases to consider the work characteristics of the modular plant. The predicted contingency is that 6.739%(Engineering 2.850%, Procurement 6.225%, Fabrication 6.211%, Transportation 4.165%, Construction 8.168%) to prepare the basic business expense. The model is used as a way to derive quantitative results in the decision-making process for risk management in construction projects.

Failure estimation of the composite laminates using machine learning techniques

  • Serban, Alexandru
    • Steel and Composite Structures
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    • v.25 no.6
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    • pp.663-670
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    • 2017
  • The problem of layup optimization of the composite laminates involves a very complex multidimensional solution space which is usually non-exhaustively explored using different heuristic computational methods such as genetic algorithms (GA). To ensure the convergence to the global optimum of the applied heuristic during the optimization process it is necessary to evaluate a lot of layup configurations. As a consequence the analysis of an individual layup configuration should be fast enough to maintain the convergence time range to an acceptable level. On the other hand the mechanical behavior analysis of composite laminates for any geometry and boundary condition is very convoluted and is performed by computational expensive numerical tools such as finite element analysis (FEA). In this respect some studies propose very fast FEA models used in layup optimization. However, the lower bound of the execution time of FEA models is determined by the global linear system solving which in some complex applications can be unacceptable. Moreover, in some situation it may be highly preferred to decrease the optimization time with the cost of a small reduction in the analysis accuracy. In this paper we explore some machine learning techniques in order to estimate the failure of a layup configuration. The estimated response can be qualitative (the configuration fails or not) or quantitative (the value of the failure factor). The procedure consists of generating a population of random observations (configurations) spread across solution space and evaluating using a FEA model. The machine learning method is then trained using this population and the trained model is then used to estimate failure in the optimization process. The results obtained are very promising as illustrated with an example where the misclassification rate of the qualitative response is smaller than 2%.

Effect of axial loading conditions and confinement type on concrete-steel composite behavior

  • Nematzadeh, Mahdi;Fazli, Saeed
    • Computers and Concrete
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    • v.25 no.2
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    • pp.95-109
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    • 2020
  • This paper aims to analytically study the effect of loading conditions and confinement type on the mechanical properties of the concrete-steel composite columns under axial compressive loading. The axial loading is applied to the composite columns in the two ways; only on the concrete core, and on the concrete core and steel tube simultaneously, which are called steel tube-confined concrete (STCC) and concrete-filled steel tube (CFST) columns, respectively. In addition, the confinement is investigated in the three types of passive, short-term active and long-term active confinement. Nonlinear finite element 3D models for analyzing these columns are developed using the ABAQUS program, and then these models are verified with respect to the recent experimental results reported by the authors on the STCC and CFST columns experiencing active and passive confinements. Axial and lateral stress-strain curves as well as the failure mode for qualitative verification, and compressive strength for quantitative verification are considered. It is found that there is a good consistency between the finite element analysis results and the experimental ones. In addition, a parametric study is performed to evaluate the effect of axial loading type, prestressing ratio, concrete compressive strength and steel tube diameter-to-wall thickness ratio on the compressive behavior of the composite columns. Finally, the compressive strength results of CFST specimens obtained via the finite element analysis are compared with the values specified by the international codes and standards including EC4, CSA, ACI-318, and AISC, with the results showing that ACI-318 and AISC underestimate the compressive strength of the composite columns, while EC4 and CSA codes present overestimated values.

Hydrological Variability of Lake Chad using Satellite Gravimetry, Altimetry and Global Hydrological Models

  • Buma, Willibroad Gabila;Seo, Jae Young;Lee, Sang-IL
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.467-467
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    • 2015
  • Sustainable water resource management requires the assessment of hydrological variability in response to climate fluctuations and anthropogenic activities. Determining quantitative estimates of water balance and total basin discharge are of utmost importance to understand the variations within a basin. Hard-to-reach areas with few infrastructures, coupled with lengthy administrative procedures makes in-situ data collection and water management processes very difficult and unreliable. In this study, the hydrological behavior of Lake Chad whose extent, extreme climatic and environmental conditions make it difficult to collect field observations was examined. During a 10 year period [January 2003 to December 2013], dataset from space-borne and global hydrological models observations were analyzed. Terrestial water storage (TWS) data retrieved from Gravity Recovery and Climate Experiment (GRACE), lake level variations from Satellite altimetry, water fluxes and soil moisture from Global Land Data Assimilation System (GLDAS) were used for this study. Furthermore, we combined altimetry lake volume with TWS over the lake drainage basin to estimate groundwater and soil moisture variations. This will be validated with groundwater estimates from WaterGAP Global Hydrology Model (WGHM) outputs. TWS showed similar variation patterns Lake water level as expected. The TWS in the basin area is governed by the lake's surface water. As expected, rainfall from GLDAS precedes GRACE TWS with a phase lag of about 1 month. Estimates of groundwater and soil moisture content volume changes derived by combining altimetric Lake Volume with TWS over the drainage basin are ongoing. Results obtained shall be compared with WaterGap Hydrology Model (WGHM) groundwater estimate outputs.

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