• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.397-419
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• 2017

A four-parameter extended fatigue lifetime model called the odd Birnbaum-Saunders geometric distribution is proposed. This model extends the odd Birnbaum-Saunders and Birnbaum-Saunders distributions. We derive some properties of the new distribution that include expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood and a Bayesian approach are adopted to estimate the model parameters; in addition, various simulations are performed for different parameter settings and sample sizes. We propose two new models with a cure rate called the odd Birnbaum-Saunders mixture and odd Birnbaum-Saunders geometric models by assuming that the number of competing causes for the event of interest has a geometric distribution. The applicability of the new models are illustrated by means of ethylene data and melanoma data with cure fraction.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2005.06a
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• pp.54-62
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• 2005

While genomics (the set of experimental and computational tools that allows the blueprints of life to be read) opens the doors to a more rational approach to the design and use of living cells to bring about desirable chemical transformations, genomics is, by itself, insufficient. We need tools that allow us to relate genomic and molecular information to cellular physiology and then to the response of a population of cells. We propose the development of hybrid computer cellular models. In such models genomics and chemical detail for a cellular subsystem (e.g. pathogenesis) is embedded in a coarse-grain cell model. Such a construct allows the quantitative and explicit linkage of genomic detail to cell physiology to the extracellular environment. To illustrate the principles involved we are constructing a model for a minimal cell. A minimal cell is a bacterial cell with the fewest number of genes necessary to sustain life as a free living microbe.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1225-1239
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• 2016

We investigate pediatric tumor incidence data collected by the Florida Association for Pediatric Tumor program using various models commonly used in disease mapping analysis. Particularly, we consider Poisson normal models with various conditional autoregressive structure for spatial dependence, a zero-in ated component to capture excess zero counts and a spatio-temporal model to capture spatial and temporal dependence, together. We found that intrinsic conditional autoregressive model provides the smallest Deviance Information Criterion (DIC) among the models when only spatial dependence is considered. On the other hand, adding an autoregressive structure over time decreases DIC over the model without time dependence component. We adopt weighted ranks squared error loss to identify high risk regions which provides similar results with other researchers who have worked on the same data set (e.g. Zhang et al., 2014; Wang and Rodriguez, 2014). Our results, thus, provide additional statistical support on those identied high risk regions discovered by the other researchers.

• Advances in Traditional Medicine
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• v.8 no.3
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• pp.260-265
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• 2008

Annona reticulata belonging to the family Annonaceae is traditionally used as anthelmintic and it is reported to have anticancer activity. Free radicals are known to be involved in various types of diseases like cancer, diabetes, neurological disorders etc. The present study was aimed to evaluate free radical scavenging property of methanol extract of the leaves of Annona reticulata in some in vitro models e.g. DPPH, nitric oxide, superoxide and lipid peroxide radical model. The extract showed good dose-dependent free radical scavenging property in all the models. $IC_{50}$ values were found to be 3.22, 170.01, 25.12 and $140.12\;{\mu}g/ml$ respectively in DPPH, nitric oxide, superoxide and lipid peroxidation inhibition assays. Reductive ability of the extract was also tested based on potassium ferricyanide reduction where dose dependant reducing capability was observed. Measurement of total phenolic compounds by Folin-Ciocalteu's phenol reagent indicated that 1mg of the extract contained $146.20\;{\mu}g$ equivalent of pyrocatechol. The findings ascertain promising free radical scavenging property of the extract and the antioxidant property of the extract may be due to the high content of phenolic compounds.

• Environmental Engineering Research
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• v.19 no.3
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• pp.247-253
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• 2014

The aim of this study was to characterize quintinite in fluoride removal from aqueous solutions, using batch experiments. Experimental results showed that the maximum adsorption capacity of fluoride to quintinite was 7.71 mg/g. The adsorption of fluoride to quintinite was not changed at pH 5-9, but decreased considerably in highly acidic (pH < 3) and alkaline (pH > 11) solution conditions. Kinetic model analysis showed that among the three models (pseudo-first-order, pseudo-second-order, and Elovich), the pseudo-second-order model was the most suitable for describing the kinetic data. From the nonlinear regression analysis, the pseudo-second-order parameter values were determined to be $q_e=0.18mg/g$ and $k_2=28.80g/mg/hr$. Equilibrium isotherm model analysis demonstrated that among the three models (Langmuir, Freundlich, and Redlich-Peterson), both the Freundlich and Redlich-Peterson models were suitable for describing the equilibrium data. The model analysis superimposed the Redlich-Peterson model fit on the Freundlich fit. The Freundlich model parameter values were determined from the nonlinear regression to be $K_F=0.20L/g$ and 1/n=0.51. This study demonstrated that quintinite could be used as an adsorbent for the removal of fluoride from aqueous solutions.

• Smart Structures and Systems
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• v.20 no.3
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• pp.385-396
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• 2017

The recent advancements in sensing technologies allow us to record measurements from target structures at multiple locations and with relatively high spatial resolution. Such measurements can be used to develop data-driven methodologies for condition assessment, control, and health monitoring of target structures. One of the state-of-the-art technologies, Fiber Optic Strain Sensors (FOSS), is developed at NASA Armstrong Flight Research Center, and is based on Fiber Bragg Grating (FBG) sensors. These strain sensors are accurate, lightweight, and can provide almost continuous strain-field measurements along the length of the fiber. The strain measurements can then be used for real-time shape-sensing and operational load-estimation of complex structural systems. While several works have demonstrated the successful implementation of FOSS on large-scale real-life aerospace structures (i.e., airplane wings), there is paucity of studies in the literature that have investigated the potential of extending the application of FOSS into civil structures (e.g., tall buildings, bridges, etc.). This work assesses the feasibility of using FOSS to predict operational loads (e.g., wind loads) on chain-like structures. A thorough investigation is performed using analytical, computational, and experimental models of a 4-story steel building test specimen, developed at the University of Southern California. This study provides guidelines on the implementation of the FOSS technology on building-like structures, addresses the associated technical challenges, and suggests potential modifications to a load-estimation algorithm, to achieve a robust methodology for predicting operational loads using strain-field measurements.

• Geomechanics and Engineering
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• v.3 no.4
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• pp.291-321
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• 2011

The paper describes a simple numerical FLAC model that was developed to simulate the dynamic response of two instrumented reduced-scale model reinforced soil walls constructed on a 1-g shaking table. The models were 1 m high by 1.4 m wide by 2.4 m long and were constructed with a uniform size sand backfill, a polymeric geogrid reinforcement material with appropriately scaled stiffness, and a structural full-height rigid panel facing. The wall toe was constructed to simulate a perfectly hinged toe (i.e. toe allowed to rotate only) in one model and an idealized sliding toe (i.e. toe allowed to rotate and slide horizontally) in the other. Physical and numerical models were subjected to the same stepped amplitude sinusoidal base acceleration record. The material properties of the component materials (e.g. backfill and reinforcement) were determined from independent laboratory testing (reinforcement) and by back-fitting results of a numerical FLAC model for direct shear box testing to the corresponding physical test results. A simple elastic-plastic model with Mohr-Coulomb failure criterion for the sand was judged to give satisfactory agreement with measured wall results. The numerical results are also compared to closed-form solutions for reinforcement loads. In most cases predicted and closed-form solutions fall within the accuracy of measured loads based on ${\pm}1$ standard deviation applied to physical measurements. The paper summarizes important lessons learned and implications to the seismic design and performance of geosynthetic reinforced soil walls.

• The korean journal of orthodontics
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• v.42 no.4
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• pp.159-168
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• 2012

Objective: The aims of this study were to investigate mandibular deformation under clenching and to estimate its effect on the stability of orthodontic mini-implants (OMI). Methods: Three finite element models were constructed using computed tomography (CT) images of 3 adults with different mandibular plane angles (A, low; B, average; and C, high). An OMI was placed between #45 and #46 in each model. Mandibular deformation under premolar and molar clenching was simulated. Comparisons were made between peri-orthodontic mini-implant compressive strain (POMI-CSTN) under clenching and orthodontic traction forces (150 g and 200 g). Results: Three models with different mandibular plane angles demonstrated different functional deformation characteristics. The compressive strains around the OMI were distributed mesiodistally rather than occlusogingivally. In model A, the maximum POMI-CSTN under clenching was observed at the mesial aspect of #46 (1,401.75 microstrain [${\mu}E$]), and similar maximum POMI-CSTN was observed under a traction force of 150 g (1,415 ${\mu}E$). Conclusions: The maximum POMI-CSTN developed by clenching failed to exceed the normally allowed compressive cortical bone strains; however, additional orthodontic traction force to the OMI may increase POMI-CSTN to compromise OMI stability.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.3
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• pp.33-38
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• 2021

Recently, transfer learning techniques with a base convolutional neural network (CNN) model have widely gained acceptance in early detection and classification of crop diseases to increase agricultural productivity with reducing disease spread. The transfer learning techniques based classifiers generally achieve over 90% of classification accuracy for crop diseases using dataset of crop leaf images (e.g., PlantVillage dataset), but they have ability to classify only the pre-trained diseases. This paper provides with an evaluation scheme on selecting an effective base CNN model for crop disease transfer learning with regard to the accuracy of trained target crops as well as of untrained target crops. First, we present transfer learning models called CDC (crop disease classification) architecture including widely used base (pre-trained) CNN models. We evaluate each performance of seven base CNN models for four untrained crops. The results of performance evaluation show that the DenseNet201 is one of the best base CNN models.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.89-96
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• 2001

Agent-mediated electronic markets have been a grow-ing area of agent research and developmen tin recent year. There exist a lot of e-commerce sites on the In-ternet(e.g. Priceline, com, Amazon, com etc). These e-commerce site have proposed new business models for effective and efficient commerce activity. Intelli-gent agents have been studied very widely in the field of artificial intelligence, For purpose of this paper, an agent can act autonomously and collaboratively in a network environment on behalf of its users. It is hard for people to effectively and efficiently monitor, buy, and sell at multiple e-commerce sites. If we intro-duce agent technologies into e-commerce systems, we can expect to further enhance the intelligence of their support. In this paper, we propose a new coopera-tion mechanism among seller agents based on exchang-ing their goods in our agent-mediated electronic market system. G-Commerce. On G-Commerce, seller agents and buyer agents negotiate with each other. In our model, seller agents cooperatively negotiate in order to effectively sell goods in stock. Buyer agents coopera-tively form coalitions in order to buy goods based an discount proices. Seller agent's negotiation goods. Our current experiments show that exchanging mechanism enables seller agents to effectively sell goods in stock. Also, we present the Pareto optimality of our exchang-ing mechanism.