• Title/Summary/Keyword: Quantitative structure model

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- A Decision Model for Outsourcing Using AHP - (AHP를 이용한 아웃소싱 의사결정모형)

  • 우태희;임충묵
    • Journal of the Korea Safety Management & Science
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    • v.5 no.2
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    • pp.175-185
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    • 2003
  • Information systems(IS) outsourcing has become a very important management strategy of implementing IS and many studies on the IS outsourcing approach had been performed in the organizations. But it isn't still show how to out source the IS functions and how to offer quantitative magnitude for judgement. To offer a quantitative decision model that can help practitioners set priority and reap the most benefits from outsourcing, we show outsourcing structure including 3 factors (strategic, economic and technological benefit) and sub-levels which is different from the Yang and Huang's model. Also, we compute the weight of alternatives using analytic hierarchy process to find a priority of the IS outsourcing. As a result of analysis, we suggest systematic steps and quantitative model to increase the precision of decision making. 1)

A Decision Model for Information Systems Outsourcing Using AHP (AHP를 이용한 정보시스템 아웃소싱 의사결정모형)

  • 우태희;임충묵
    • Proceedings of the Safety Management and Science Conference
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    • 2003.05a
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    • pp.37-42
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    • 2003
  • Recently, information systems(IS) outsourcing has become a very important management strategy of implementing IS and many studies on the IS outsourcing approach had been largely performed in the organizations, but it isn't still show how to outsource the IS functions and how to decide quantitative magnitude for judgement. To offer a quantitative decision model that can help practitioners set priority and reap the most benefits from outsourcing, we show outsourcing structure including 3 factors(strategic benefit, economic benefit and technological benefit) and sub-levels which. is different from the Yang and Huang's model. Also, we compute the weight of alternatives using analytic hierarchy process to find a priority of the IS outsourcing. As a result of analysis, we suggest systematic steps and quantitative model to increase the precision of decision making.

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Quantitative-Structure Activity Relationship (QSAR) Model for Abuse-liability Evaluation of Designer Drugs (합성마약류의 의존성 평가를 위한 구조활성상관(QSAR) 모델 적용)

  • Yun, Jaesuk
    • YAKHAK HOEJI
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    • v.58 no.1
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    • pp.53-57
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    • 2014
  • In recent, the abuse of newly-emerging psychoactive drugs, ('designer drugs') is a rapidly increasing problem in Korean society. Quantitative-structure activity relationship (QSAR) is an alternative method to predict bioactivities of new abused compounds. In this study, cathinone-related new designer drugs, 4-methylbuphedrone and 4-methoxy-N,N-dimethylcathinone were tested for prediction of the bioactivity with QSAR model. The bioactivity of 4-methylbuphedrone and 4-methoxy-N,N-dimethylcathinone was similar to those of methylone. These results suggest that the prediction with QSAR model may provide scientific evidences for regulatory decision.

Human performance models using neural network

  • Kwahk, Ji-Young;Han, Sung-H.
    • Journal of the Ergonomics Society of Korea
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    • v.15 no.2
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    • pp.157-163
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    • 1996
  • A single line display menu (SDM) is widely used for the user interface of many electronic consumer products, and the designers need useful guidelines applicable to the SDM. In many studies on menus, major focus has been placed on the optimal menu structure, but only a few standard menu structures, such as $64^{1},8^{2},4^{3}$,and $2^{6}$ are usually tested for optimality. In many cases, however, ill defined or asymmetric structures are suggested as design alternatives. To determine the optimal menu structure, user performance should be obtained in terms of quantitative measures. Hence, a model is needed to provide a predicted value of user performance for a given menu structure. Altough several models have been proposed for ordinary menus, none is available for the SDM yet. To solve this problem a performance model was developed in this study using the neural network approach. This model is capable of providing quantitative measures of human performance for any menu structures without conducting additional experiments, which will save much time and reduce the design cost.

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Toxicokinetic and Toxicodynamic Models for Ecological Risk Assessment (생태위해성 평가를 위한 독성동태학 및 독성역학 모델)

  • Lee, Jong-Hyeon
    • Environmental Analysis Health and Toxicology
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    • v.24 no.2
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    • pp.79-93
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    • 2009
  • 오염물질에 대한 생태위해성평가(ecological risk assessment)를 위해서는 노출평가(exposure assessment)와 함께 생물영향에 대한 평가(effect assessment)를 수행해야 한다. 노출평가의 경우는 지화학적 과정에 대한 이해를 바탕으로 환경농도를 예측하기 위한 화학평형모델이나 다매체환경거동모델 등 다양한 평가 및 예측모델을 활용해 왔다. 이와 달리 생물영향평가는 실험실 조건에서 제한된 독성자료를 대상으로 외부노출농도에 기반한 농도-반응관계를 통계적 방법을 통해서 추정하는 '경험적 모델(empirical model)'에 주로 의존해 왔다. 최근에 와서 생체 내 잔류량을 기반으로 농도-시간-반응관계를 기술하고 예측하는 독성동태학 및 독성역학 모델(toxicokinetic-toxicodynamic model)과 같은 독성작용에 기반한 모델(processbased model)들이 개발되어 활용되고 있다. 본 논문에서는 여러 종류의 독성동태학 및 독성역학 모델을 소개하고, 이를 통계적 추론에 기반한 전통적인 독성학 모델과 비교하였다. 서로 다른 종류의 독성동태학 및 독성역학 모델로부터 도출된 노출농도-시간 -반응관계식을 비교하고, 동일 독성기작을 보이는 오염물질 그룹 내에서 미측정 오염물질의 독성을 예측할 수 있게 해주는 구조-활성관계(Quantitative Structure-Activity Relationship, QSAR) 모델을 여러 독성동태 및 독성역학모델로부터 유도하였다. 마지막으로 독성동태학 및 독성역학 파라미터를 추정하기 위한 실험계획을 제안하였고, 앞으로 독성동태학 및 독성역학 모델을 생태계 위해성평가에 활용하기 위해서 해결해야 될 연구과제를 검토하였다.

Quantitative Structure-Activity Relationships and Molecular Docking Studies of P56 LCK Inhibitors

  • Bharatham, Nagakumar;Bharatham, Kavitha;Lee, Keun-Woo
    • Bulletin of the Korean Chemical Society
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    • v.27 no.2
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    • pp.266-272
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    • 2006
  • Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 67 molecules of 2-amino-benzothiazole-6-anilide derivatives against lymphocyte-specific protein tyrosine kinase (P56 LCK). The molecular field analysis (MFA) and receptor surface analysis (RSA) were employed for QSAR studies and the predictive ability of the model was validated by 15 test set molecules. Structure-based investigations using molecular docking simulation were performed with the crystal structure of P56 LCK. Good correlation between predicted fitness scores versus observed activities was demonstrated. The results suggested that the nature of substitutions at the 2-amino and 6-anilide positions were crucial in enhancing the activity, thereby providing new guidelines for the design of novel P56 LCK inhibitors.

A Study on the Quantitative Analysis and Estimation for Surround Building caused by Vapor Cloud Explosion(VCE) in LPG Filling Station (LPG충전소에서 증기운폭발이 주변건물에 미치는 영향의 정량적 해석 및 평가에 관한 연구)

  • Leem, Sa-Hwan;Huh, Yong-Jeong
    • Journal of the Korean Society of Safety
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    • v.25 no.1
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    • pp.44-49
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    • 2010
  • This paper is estimation of structure damage caused by Explosion in LPG(Liquefied Petroleum Gas) filling station. As we estimate the influence of damage which occur at gas storage tank in filling station. We can utilize the elementary data of safety distance. In this study, the influence of over-pressure caused by VCE(Vapor Cloud Explosion) in filling station was calculated by using the Hopkinson's scaling law and the accident damage was estimated by applying the influence on the adjacent structure into the probit model. As a result of the damage estimation conducted by using the probit model, both the damage possibility of explosion overpressure to structures of max 265 meters away and to glass bursting of 1150 meters away was nearly zero in open space explosion.

Prediction of Solvent Effects on Rate Constant of [2+2] Cycloaddition Reaction of Diethyl Azodicarboxylate with Ethyl Vinyl Ether Using Artificial Neural Networks

  • Habibi-Yangjeh, Aziz;Nooshyar, Mahdi
    • Bulletin of the Korean Chemical Society
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    • v.26 no.1
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    • pp.139-145
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    • 2005
  • Artificial neural networks (ANNs), for a first time, were successfully developed for the modeling and prediction of solvent effects on rate constant of [2+2] cycloaddition reaction of diethyl azodicarboxylate with ethyl vinyl ether in various solvents with diverse chemical structures using quantitative structure-activity relationship. The most positive charge of hydrogen atom (q$^+$), dipole moment ($\mu$), the Hildebrand solubility parameter (${\delta}_H^2$) and total charges in molecule (q$_t$) are inputs and output of ANN is log k$_2$ . For evaluation of the predictive power of the generated ANN, the optimized network with 68 various solvents as training set was used to predict log k$_2$ of the reaction in 16 solvents in the prediction set. The results obtained using ANN was compared with the experimental values as well as with those obtained using multi-parameter linear regression (MLR) model and showed superiority of the ANN model over the regression model. Mean square error (MSE) of 0.0806 for the prediction set by MLR model should be compared with the value of 0.0275 for ANN model. These improvements are due to the fact that the reaction rate constant shows non-linear correlations with the descriptors.

FLASH FLOOD FORECASTING USING REMOTELY SENSED INFORMATION AND NEURAL NETWORKS PART II : MODEL APPLICATION

  • Kim, Gwang-seob;Lee, Jong-Seok
    • Water Engineering Research
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    • v.3 no.2
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    • pp.123-134
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    • 2002
  • A developed Quantitative Flood Forecasting (QFF) model was applied to the mid-Atlantic region of the United States. The model incorporated the evolving structure and frequency of intense weather systems of the study area for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters associated with synoptic atmospheric conditions as Input. Here, we present results from the application of the Quantitative Flood Forecasting (QFF) model in 2 small watersheds along the leeward side of the Appalachian Mountains in the mid-Atlantic region. Threat scores consistently above 0.6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 40% and up to 55 % were obtained.

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Racemic Descriptors for Quantitative Structure Activity Relationship of Spirosuccinimide Type Aldose Reductase Inhibitors

  • Kim, Jeong-Rim;Won, Young-Do
    • Bulletin of the Korean Chemical Society
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    • v.25 no.12
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    • pp.1874-1876
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    • 2004
  • Quantitative structure activity relationship has been probed for spirosuccinimide-fused tetrahydropyrrolo[1,2-a]pyrazine-1,3-dione derivatives acting as aldose reductase inhibitors. While the spirosuccinimide compounds contain a chiral center, the aldose reductase inhibition assay was performed with racemic mixtures in the published work. As the physicochemical descriptors of the QSAR analysis must be evaluated for a definite molecular structure, we devise a new 'racemic' descriptor as the arithmetic mean of the (R)-enantiomer descriptor and the (S)-enantiomer descriptor. The resultant QSAR model derived from the racemic descriptors outperforms the original QSAR models, closely reproducing the observed activity of optically pure enantiomers as well as racemic mixtures.