• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.1-9
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• 2016

In this paper, we propose a new learning control scheme for various walk motion control of biped robot with same learning-base by neural network. We show that learning control algorithm based on the neural network is significantly more attractive intelligent controller design than previous traditional forms of control systems. A multi layer back propagation neural network identification is simulated to obtain a dynamic model of biped robot. Once the neural network has learned, the other neural network control is designed for various trajectory tracking control with same learning-base. The biped robots have been received increased attention due to several properties such as its human like mobility and the high-order dynamic equation. These properties enable the biped robots to perform the dangerous works instead of human beings. Thus, the stable walking control of the biped robots is a fundamentally hot issue and has been studied by many researchers. However, legged locomotion, it is difficult to control the biped robots. Besides, unlike the robot manipulator, the biped robot has an uncontrollable degree of freedom playing a dominant role for the stability of their locomotion in the biped robot dynamics. From the simulation and experiments the reliability of iterative learning control was illustrated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2827-2848
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• 2012

Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.254-262
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• 2009

As the trend of e-business activities develop, customers come into contact with products through on-line shopping sites and lots of customers refer product reviews before the purchasing on-line. However, as the volume of product reviews grow, it takes a great deal of time and effort for customers to read and evaluate voluminous product reviews. Lately, attention is being paid to Opinion Mining(OM) as one of the effective solutions to this problem. In this paper, we propose an efficient method for opinion sentiment classification of product reviews using product specific context information of words occurred in the reviews. We define the context information of words and propose the application of context for sentiment classification and we show the performance of our method through the experiments. Additionally, in case of word corpus construction, we propose the method to construct word corpus automatically using the review texts and review scores in order to prevent traditional manual process. In consequence, we can easily get exact sentiment polarities of opinion words in product reviews.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.13-21
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• 2002

Fuzzy logic ignores some information in the reasoning process. Neural network is powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule-inference network. And the traditional propagation rule is modified. Experiments are performed to compare search costs by sequential searching and searching by priority. The experimental results show that the searching by priority is more efficient than the sequential searching as the size of the fuzzy inference network becomes larder and an the number of searching increases.

• Journal of Applied Reliability
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• v.18 no.3
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• The Korean Journal of Physiology and Pharmacology
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• v.21 no.1
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• pp.27-36
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• 2017

Angelicae Gigantis Radix (AGR, Angelica gigas) has been used for a long time as a traditional folk medicine in Korea and oriental countries. Decursinol angelate (DCA) is structurally isomeric decursin, one of the major components of AGR. This study was performed to confirm whether DCA augments pentobarbital-induced sleeping behaviors via the activation of $GABA_A$-ergic systems in animals. Oral administration of DCA (10, 25 and 50 mg/kg) markedly suppressed spontaneous locomotor activity. DCA also prolonged sleeping time, and decreased the sleep latency by pentobarbital (42 mg/kg), in a dose-dependent manner, similar to muscimol, both at the hypnotic (42 mg/kg) and sub-hypnotic (28 mg/kg) dosages. Especially, DCA increased the number of sleeping animals in the sub-hypnotic dosage. DCA (50 mg/kg, p.o.) itself modulated sleep architectures; DCA reduced the counts of sleep/wake cycles. At the same time, DCA increased total sleep time, but not non-rapid eye movement (NREM) and rapid eye movement (REM) sleep. In the molecular experiments. DCA (0.001, 0.01 and $0.1{\mu}g/ml$) increased intracellular Cl- influx level in hypothalamic primary cultured neuronal cells of rats. In addition, DCA increased the protein expression of glutamic acid decarboxylase ($GAD_{65/67}$) and $GABA_A$ receptors subtypes. Taken together, these results suggest that DCA potentiates pentobarbital-induced sleeping behaviors through the activation of $GABA_A$-ergic systems, and can be useful in the treatment of insomnia.

• Journal of Pharmacopuncture
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• v.18 no.4
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• pp.38-44
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• 2015

Objectives: Radix Ginseng has been used for thousands of years to treat a wide variety of diseases. Radix ginseng has also been used as a traditional medicine for boosting Qi energy and tonifying the spleen and lungs. Traditionally, its effect could be obtained orally. Nowadays, a new method, the injection of herbal medicine, is being used. This study was performed to investigate the single-dose intravenous toxicity of water-soluble ginseng pharmacopuncture (WSGP) in Sprague-Dawley (SD) rats. Methods: All experiments were carried out at Biotoxtech, an institute authorized to perform non-clinical studies under the regulation of Good Laboratory Practice (GLP). At the age of six weeks, 40 SD rats, 20 male rats and 20 female rats, were allocated into one of 4 groups according to the dosages they would receive. The WSGP was prepared in the Korean Pharmacopuncture Institute under the regulation of Korea-Good Manufacturing Practice (K-GMP). Dosages of WSGP were 0.1, 0.5 and 1.0 mL/animal for the experimental groups, and normal saline was administered to the control group. The rat's general conditions and body weights, the results of their hematological and biochemistry tests, and their necropsy and histopathological findings were investigated to identify the toxicological effect of WSGP injected intravenously. The effect was examined for 14 days after the WSGP injection. This study was performed under the approval of the Institutional Animal Ethics Committee of Biotoxtech. Results: No deaths were found in this single-dose toxicity test on the intravenous injection of WSGP, and no significant changes in the rat's general conditions and body weights, the results on their hematological and biochemistry test, and their necropsy findings were observed during the test. The local area of the injection site showed minial change. The lethal dose was assumed to be over 1.0 mL/animal in both sexes. Conclusion: These results indicate that WSGP is safe at dosages up to 1 mL/animal.

• Nutrition Research and Practice
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• v.9 no.6
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• pp.606-612
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• 2015

BACKGROUND/OBJECTIVES: Several medicinal properties of Smilax china L. have been studied including antioxidant, anti-inflammatory, and anti-cancer effects. However, the antiobesity activity and mechanism by which the water-soluble fraction of this plant mediates its effects are not clear. In the present study, we investigated the lipolytic actions of the water-soluble fraction of Smilax china L. leaf ethanol extract (wsSCLE) in 3T3-L1 adipocytes. MATERIALS/METHODS: The wsSCLE was identified by measuring the total polyphenol and flavonoid content. The wsSCLE was evaluated for its effects on cell viability, lipid accumulation, glycerol, and cyclic adenosine monophosphate (cAMP) contents. In addition, western blot analysis was used to evaluate the effects on protein kinase A (PKA), PKA substrates (PKAs), and hormone-sensitive lipase (HSL). For the lipid accumulation assay, 3T3-L1 adipocytes were treated with different doses of wsSCLE for 9 days starting 2 days post-confluence. In other cell experiments, mature 3T3-L1 adipocytes were treated for 24 h with wsSCLE. RESULTS: Results showed that treatment with wsSCLE at 0.05, 0.1, and 0.25 mg/mL had no effect on cell morphology and viability. Without evidence of toxicity, wsSCLE treatment decreased lipid accumulation compared with the untreated adipocyte controls as shown by the lower absorbance of Oil Red O stain. The wsSCLE significantly induced glycerol release and cAMP production in mature 3T3-L1 cells. Furthermore, protein levels of phosphorylated PKA, PKAs, and HSL significantly increased following wsSCLE treatment. CONCLUSION: These results demonstrate that the potential antiobesity activity of wsSCLE is at least in part due to the stimulation of cAMP-PKA-HSL signaling. In addition, the wsSCLE-stimulated lipolysis induced by the signaling is mediated via activation of the ${\beta}$-adrenergic receptor.

• Journal of the Korean Institute of Rural Architecture
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• v.20 no.2
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• pp.29-36
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• 2018

Even in modern times, we are accustomed to the lifestyle of floor heating system in which the floor is heated for warmth like Ondol, which is the traditional Korean heating system. So, this study was designed to understand the preferred floor temperature through the questionnaires targeting the local residents living in K region. This study would also find out the floor temperature which is preferred by young people and old people through the experiments. The findings are as follows; (1) the old people do not prefer the temperature higher than young people do. It was found that the old people prefer the floor temperature of $40^{\circ}C$ under the air temperature of $20^{\circ}C$ or the floor temperature of $41^{\circ}C$ under the air temperature of $20^{\circ}C$. (2) Both young people and old people tend to like the average skin temperature of $35.5^{\circ}C$. The skin temperature which both young and old people like was $35.2^{\circ}C$ under the air temperature of $24^{\circ}C$ and the skin temperature preferred by young people was $0.4^{\circ}C$ higher than that preferred by under the air temperature of $20^{\circ}C$ (p<0.01). (3) It was found in the questionnaires that the young people prefer the higher floor temperature in terms of age and that the people who get older in their 50s or higher tend to prefer the lower temperature.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.267-283
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• 2007

In this study, measures of distributional similarity such as KL-divergence are applied to cluster documents instead of traditional cosine measure, which is the most prevalent vector similarity measure for document clustering. Three variations of KL-divergence are investigated; Jansen-Shannon divergence, symmetric skew divergence, and minimum skew divergence. In order to verify the contribution of distributional similarities to document clustering, two experiments are designed and carried out on three test collections. In the first experiment the clustering performances of the three divergence measures are compared to that of cosine measure. The result showed that minimum skew divergence outperformed the other divergence measures as well as cosine measure. In the second experiment second-order distributional similarities are calculated with Pearson correlation coefficient from the first-order similarity matrixes. From the result of the second experiment, secondorder distributional similarities were found to improve the overall performance of document clustering. These results suggest that minimum skew divergence must be selected as document vector similarity measure when considering both time and accuracy, and second-order similarity is a good choice for considering clustering accuracy only.