• Nuclear Medicine and Molecular Imaging
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• v.42 no.2
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• pp.112-117
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• 2008

Artifact corrections including normalization and attenuation correction were important for quantitative analysis in Nuclear Medicine Imaging. Normalization is the process of ensuring that all lines of response joining detectors in coincidence have the same effective sensitivity. Failure to account for variations in LOR sensitivity leads to bias and high-frequency artifacts in the reconstructed images. Attenuation correction is the process of the correction of attenuation phenomenon lies in the natural property that photons emitted by the radiopharmaceutical will interact with tissue and other materials as they pass through the body. In this paper, we will review the several approaches for normalization and attenuation correction strategies.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.183-186
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• 2010

Advanced Railway countries are developing technologies of production and management for low-carbon and green growth of their railway industry to hold a dominant position under post-Tokyo protocol regime through integrated approach which uses environmental quantitative analysis of train life cycle by using LCA(Life Cycle Assessment). On the contrary, Korea railroad industry attempts to make an environmental improvement only for using regenerative energy and improvement in operating energy consumption through adapting reduction weight of material technology and etc. without systematic environmental analysis approaches such as comparing and analyzing energy consumption as well as GHG emission in each life cycle stages of train. Therefore, In this paper, low-carbon management and comprehensive environmental improvement for sustainable development of Korea railway industry through analyzing the result of life cycle analysis in abroad are suggested.

• Journal of Korean Elementary Science Education
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• v.19 no.1
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• pp.71-83
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• 2000

This study examined the influences of science project activities based on multiple intelligences on problem solving behaviors of elementary school children. Specifically, the influences of the project activities on the problem solving skills and propensities of the children were investigated. Forty-four fifth graders were selected for the study. They performed the projects and made their products of it during five months on the units of "Weather" and "Our Body" Criteria for assessment of problem solving abilities were determined. The patterns reflected in products of the project activities were examined, then the observation of the subjects' problem solving behaviors and the interviews were performed based on the criteria. The results were analyzed through both of qualitative and quantitative approaches. In these analyses, the implementation of the science projects was found to contribute to the improvement in all sub-factors of problem solving, specially, skills associated with the propensities of problem identification and of the collection, analysis, and synthesis of data significantly increased

• Genomics & Informatics
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• v.5 no.1
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• pp.24-29
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• 2007

Computational virtual screening has become an essential platform of drug discovery for the efficient identification of active candidates. Moleculardocking, a key technology of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is still required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structureactivity relationship (QSAR). Our results show that the ensemble-average free energy estimation, including implicit solvation energy terms, significantly improves the hit enrichment of the virtual screening. We also demonstrate that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.

• Nuclear Medicine and Molecular Imaging
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• v.40 no.6
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• pp.279-292
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• 2006

Recent progress in the development of non-invasive imaging technologies continues to strengthen the role of biomedical research. These tools have been validated recently in variety of research models, and have born shown to provide continuous quantitative monitoring of the location(s), magnitude, and time-variation of gene delivery and/or expression. This article reviews the use of PET technologies as they have been used in imaging biological processes for molecular imaging applications. The studies published to date demonstrate that noninvasive imaging tools will help to accelerate pre-clinical model validation as well as allow for clinical monitoring of human diseases.

• Management Science and Financial Engineering
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• v.15 no.2
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• pp.101-118
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• 2009

In quantitative contexts, data mining is widely applied to the prediction of stock prices from financial time-series. However, few studies have examined the potential of data mining for shedding light on the qualitative problem-solving knowledge of experts who make stock price predictions. This paper presents a GA-based data mining approach to characterizing the qualitative knowledge of such experts, based on their observed predictions. This study is the first of its kind in the GA literature. The results indicate that this approach generates rules with higher accuracy and greater coverage than inductive learning methods or neural networks. They also indicate considerable agreement between the GA method and expert problem-solving approaches. Therefore, the proposed method offers a suitable tool for eliciting and representing expert decision rules, and thus constitutes an effective means of predicting the stock price index.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.188-195
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• 2017

The paper presents a histogram equalization method using the edge information of an image to be processed. The basic idea of this method is to carry out histogram equalization with edge information, which is important and essential for object conformation. In the proposed method, the edge information is used to generate histogram for the equalization process. It is found to be effective to suppress the histogram spikes that cause quantum jumps in mapping function for the equalization process. The proposed method is tested for randomly selected 30 images and compared to conventional approaches with a quantitative measure to check it preserves the structural similarity. Experimental results show that the proposed method has better performance and no artifacts caused by histogram spikes.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.199-199
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• 2000

Most of linear time-varying(LTV) systems except special cases have no general solution for the dynamic equations. Thus, it is difficult to design time-varying controllers in analytic ways, and other control design approaches such as robust control have been applied to control design for uncertain LTI systems which are the approximation of LTV systems have been generally used instead. A robust control method such as quantitative feedback theory(QFT) has an advantage of guaranteeing the stability and the performance specification against plant parameter uncertainties in frozen time sense. However, if these methods are applied to the approximated linear time-invariant(LTI) plants which have large uncertainty, the designed control will be constructed in complicated forms and usually not suitable for fast dynamic performance. In this paper, as a method to enhance the fast dynamic performance, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks for LTV systems with bounded time-varying parameters.

• Natural Product Sciences
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• v.10 no.4
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• pp.152-167
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• 2004

Traditional Chinese Medicines (TCM) have attracted great interest in recent researchers as alternative medicines for incurable diseases. This review focuses on qualitative and quantitative analytical approaches for bioactive metabolites of components flavonoids and saponins of traditional Chinese medicines by TLC system, although various methods have been introduced. Emphasis will be put on the processes of metabolite extraction from intestinal bacterial cultures or urines, separation (mobile phase) and detection. The identified metabolites by selection of extraction solvent and detection methods are also discussed. In addition, metabolite determinations of flavonoids (baicalin, apiin, rutin, quercetin, quercitrin, kaempferol, diosmin, hesperidin, poncirin, naringin, puerarin, daidzin, daidzein, tectoridin) and saponins (ginsenosides, kalopanaxsaponins, glycyrrhizin, chiisanoside, saikosaponins, soyasaponins) in culture fluid, in urine and in some herbal formula extracts are summarized. These bioactive metabolites of these components by intestinal microflora should be connected to pharmacological actions.

• Journal of Engineering Education Research
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• v.23 no.2
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• pp.24-30
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• 2020

This paper proposes the approaches to the evaluation of learning using concepts of artificial intelligence. Among various techniques, deep learning algorithm is employed to achieve quantitative results of evaluation. In particular, this paper focuses on the process-based evaluation instead of the result-based one using face expression. The expression is simply acquired by digital camera that records face expression when students solve sample test problems. Face expressions are trained using convolutional neural network (CNN) model followed by classification of expression data into three categories, i.e., easy, neutral, difficult. To substantiate the proposed approach, the simulation results show promising results, and this work is expected to open opportunities for intelligent evaluation system in the future.