• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.290-293
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• 2007

The land surface temperature (LST) derived from the meteorological satellite can be used to investigate the urban heat island (UHI) and its temporal variations. In this study, we developed LST retrieval algorithm from MTSAT-1R by means of a statistical regression analysis from radiative transfer simulations using MODTRAN 4 for a wide range of atmospheric, satellite viewing angle (SVA) and lapse rate conditions. 535 sets of thermodynamic initial guess retrieval (TIGR) were used for the radiative transfer simulations. Sensitivity and intercomparison results showed that the algorithm, developed in this study, estimated the LST with a similar bias and root mean square errors to that of other algorithms. The magnitude, spatial extent, and seasonal and diurnal variations of the UBI of Korean peninsula were well demonstrated by the LST derived from MTSAT-1R data. In general, the temporal variations of UHI clearly depend on the weather conditions and geographic environment of urban.

• Journal of Integrative Natural Science
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• v.3 no.1
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• pp.49-53
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• 2010

Molecular docking is a critical event which mostly forms Van der waals complex in molecular recognition. Since the majority of developed drugs are small molecules, docking them into proteins has been a prime concern in drug discovery community. Since the binding pose space is too vast to cover completely, many search algorithms such as genetic algorithm, Monte Carlo, simulated annealing, distance geometry have been developed. Proper evaluation of the quality of binding is an essential problem. Scoring functions derived from force fields handle the ligand binding prediction with the use of potential energies and sometimes in combination with solvation and entropy contributions. Knowledge-based scoring functions are based on atom pair potentials derived from structural databases. Forces and potentials are collected from known protein-ligand complexes to get a score for their binding affinities (e.g. PME). Empirical scoring functions are derived from training sets of protein-ligand complexes with determined affinity data. Because non of any single scoring function performs generally better than others, some other approaches have been tried. Although numerous scoring functions have been developed to locate the correct binding poses, it still remains a major hurdle to derive an accurate scoring function for general targets. Recently, consensus scoring functions and target specific scoring functions have been studied to overcome the current limitations.

• Journal of Ginseng Research
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• v.38 no.3
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• pp.187-193
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• 2014

Background: White ginseng (Panax ginseng Meyer) is commonly distributed as a health food in food markets. However, there is no practical method for distinguishing Korean white ginseng (KWG) from Chinese white ginseng (CWG), except for relying on the traceability system in the market. Methods: Ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with orthogonal partial least squares discrimination analysis (OPLS-DA) was employed to discriminate between KWG and CWG. Results: The origins of white ginsengs in two test sets ($1.0{\mu}L$ and $0.2{\mu}L$ injections) could be successfully discriminated by the OPLS-DA analysis. From OPLS-DA S-plots, KWG exhibited tentative markers derived from ginsenoside Rf and notoginsenoside R3 isomer, whereas CWG exhibited tentative markers derived from ginsenoside Ro and chikusetsusaponin Iva. Conclusion: Results suggest that ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with OPLS-DA is an efficient tool for identifying the difference between the geographical origins of white ginsengs.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.663-667
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• 2004

This paper presents new pruning and learning methods for the fuzzy rule-based classifier. The structure of the proposed classifier is framed from the fuzzy sets in the premise part of the rule and the Bayesian classifier in the consequent part. For the simplicity of the model structure, the unnecessary features for each fuzzy rule are eliminated through the iterative pruning algorithm. The quality of the feature is measured by the proposed correctness method, which is defined as the ratio of the fuzzy values for a set of the feature values on the decision region to one for all feature values. For the improvement of the classification performance, the parameters of the proposed classifier are finely adjusted by using the gradient descent method so that the misclassified feature vectors are correctly re-categorized. The cost function is determined as the squared-error between the classifier output for the correct class and the sum of the maximum output for the rest and a positive scalar. Then, the learning rules are derived from forming the gradient. Finally, the fuzzy rule-based classifier is tested on two data sets and is found to demonstrate an excellent performance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.11 no.4
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• pp.17-22
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• 1974

In this paper, the problem of finding tests to detect faults in combinational logic circuits is considered. At first, the method of fault detection in fan-out-free irredundant circuits is derived, and the result is extended to the fan-out redundant circuits. A fan-out circuit is decomposed into a set of fan-out-free subcircuits by cutting the lines at the internal fan-out points, and the minimal detecting test. sets for each subcircuit are found separately. And then, the compatible tests from each test set are combined maximally into composite tests to generate primary input binary vectors. By this procedure. the minimal complete test sets for reconvergent fan-out circuits are easily found and the detectable and undetectable faults are also classified clearly.

• Korean Management Science Review
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• v.28 no.1
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• pp.61-74
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• 2011

Not only the preference data but also the similarity data can be used for developing effective marketing strategies. Hahn et al.[10] proposes a methodology of representing a brand(focal brand)'s competitors in a single map called the Preference-Similarity Map, according to their relative preference to and similarity with the focal brand. They also proposes a way to derive the relative preference and similarity values from the survey collecting the choice data from differing choice sets. This study identifies the limitations of the preference and similarity measures proposed by Hahn et al.[10] and shows how these measures can be revised. This study also proposes how to implement the revised measures and analyze brands' positioning strategies. Based on the results of the previous studies on the effect of inter brand similarity on brand evaluations, this study assumes that it is important to analyze how much a specific brand is preferred to its close competitors when evaluating the effectiveness of the brand's positioning in the market. This study applies the proposed measures to the data used in Hahn et al.[10] and also show how the proposed measures are related to the parameters of the choice model proposed by Batsell and Polking[1].

• Journal of Microbiology and Biotechnology
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• v.16 no.5
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• pp.683-688
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• 2006

We have developed a program for generating shotgun data sets from known genome sequences. Generation of synthetic data sets by computer program is a useful alternative to real data to which students and researchers have limited access. Uniformly-distributed-sampling clones that were adopted by previous programs cannot account for the real situation where sampled reads tend to come from particular regions of the target genome. To reflect such situation, a probabilistic model for biased sampling distribution was developed by using an experimental data set derived from a microbial genome project. Among the experimental parameters tested (varied fragment or read lengths, chimerism, and sequencing error), the extent of sequencing error was the most critical factor that hampered sequence assembly. We propose that an optimum sequencing strategy employing different insert lengths and redundancy can be established by performing a variety of simulations.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.30.1-30.1
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• 2016

We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind, high-spatial resolution map of metallicity up to a radius of $4^{\circ}-5^{\circ}$, derived using large area photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. The RGB is identified in the V, (V - I) colour- magnitude diagrams of small subregions of varying sizes in both data sets. The slope of the RGB is used as an indicator of the mean metallicity of a subregion, and it is calibrated to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The mean metallicity of the LMC is found to be [Fe/H] = -0.37 dex (${\sigma}[Fe/H]=0.12$) from MCPS data, and [Fe/H] = -0.39 dex (${\sigma}[Fe/H]=0.10$) from OGLE III data. The bar is found to have an uniform and higher metallicity compared to the disk, and is indicative of an active bar in the past. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc ($-0.049{\pm}0.002$ dex kpc-1 to $-0.066{\pm}0.006$ dex kpc-1). This metallicity gradient of the LMC disk, though shallow, resembles the gradient seen in spiral galaxies, and similar to that found in our Galaxy.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.8 s.179
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• pp.1949-1957
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• 2000

All the loads in the real world act dynamically on structures. Since dynamic loads are extremely difficult to handle in analysis and design, static loads are utilized with dynamic factors. The dyna mic factors are generally determined based on experiences. Therefore, the static loads can cause problems in precise analysis and design. An analytical method based on modal analysis has been proposed for the transformation of dynamic loads into equivalent static load sets. Equivalent static load sets are calculated to generate an identical displacement field in a structure with that from dynamic loads at a certain time. The process is derived and evaluated mathematically. The method is verified through numerical tests. Various characteristics are identified to match the dynamic and the static behaviors. For example, the opposite direction of a dynamic load should be considered due to the vibration response. A dynamic bad is transformed to multiple equivalent static loads according to the number of the critical times. The places of the equivalent static load can be different from those of the dynamic load. An optimization method is defined to use the equivalent static loads. The developed optimization process has the same effect as the dynamic optimization which uses the dynamic loads directly. Standard examples are solved and the results are discussed

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.71-76
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• 2007

Object detection process which makes decision on the existence of meaningful objects in a given image is a crucial part of image recognition in computer vision system. Hausdorff distance metric has been used in object detection and shows good results in applications such as face recognition. It defines the dissimilarity between two sets of points and is used to find the object that is most similar to the given model. This paper proposes a Hausdorff distance based detection method that uses directional information of points to improve detection accuracy when the sets of points are derived from edge extraction as is in usual cases. In this method, elastic energy needed to make two directional points coincident is used as a measure of similarity.