• Biomedical Science Letters
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• v.25 no.4
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• pp.293-301
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• 2019

Combination chemotherapy is more effective than mono-chemotherapy and is widely used in clinical practice for enhanced cancer treatment. In this study, we investigated the potential synergistic effects of acetaminophen, a common component in many cold medicines, and romidepsin, a histone deacetylase (HDAC) inhibitor, in the A549 non-small cell lung cancer (NSCLC) cell line. The combination of acetaminophen and romidepsin also exerted significant cytotoxicity and apoptosis induced by activation of caspase-3 on tumor cells in vitro. Moreover, combination therapy significantly induced increased production of chemokines that stimulate migration of activated T-cells into tumor cells. This mechanism can lead to active T-cell mediated anti-tumor immunity in addition to the direct cytotoxic chemotherapeutic effect. Activated T-cells led to enhanced cytotoxicity in drug-treated A549 cells through interaction with tumor cells. These results suggested that the interaction between the two drugs is synergistic and significant. In conclusion, our data showed that the use of romidepsin and low concentrations acetaminophen could induce effective anti-tumor effects via enhanced tumor immune and direct cytotoxic chemotherapeutic responses. The combination of acetaminophen with romidepsin should be considered as a promising strategy for the treatment of lung cancer.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.2
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• pp.52-59
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• 2004

In this paper, the automatic system generation algorithm based on the element combination algorithm discussed in the first part of this paper for designing an arbitrary type of the automatic transmissions is proposed. The powertrain design software using these algorithms is developed. This automotive powertrain design software with user-friendly graphic user interface has two main modules. The first module, the automatic power flow generation module, is already discussed in the previous paper. The second module dealing with the automatic system generation algorithm is discussed in this paper. The power-flow simulation software fur the arbitrary type of powertrain is then developed. The simulation and experimental results of the vehicle equipped with two planetary gear type automatic transmission are compared to validate the proposed algorithms and developed software. The simulation results demonstrate the good agreement with the experimental results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.11
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• pp.957-965
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• 2013

This paper deals with analytical methods for low frequency and high frequency brake squeal noise on brake-rear caliper. In order to improve low frequency and high frequency squeal noise, we take survey caliper bracket shape parameters and housing shape parameters. Besides, using the combination of bracket and housing parameter were surveyed. Thus, using the combination of bracket Alt_05 and housing Alt_45 specifications, instability analysis and brake dynamo test were carried out. Based upon the two models, low and high frequency squeal noise of base model were improved. But, for 6.0 kHz frequency noise, which is not improved, it needs to additionally study on instability analysis and combination of the other brake components.

• Korean Journal of Food Science and Technology
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• v.26 no.1
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• pp.57-61
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• 1994

Performance of panelists trained for cooked rice quality was evaluated using analysis of variance, correlation analysis, and principal component analysis. Each method offered different information. Results showed that panleists with high F ratios (p=0.05) did not always have high correlation coefficient (p=0.05) with mean values pooled from whole panel. The results of analysis of variance for the panelists whose performance were extremely good or extremely poor were consistent with those of correlation analysis. Outliers designated by principal component analysis were different from the panelists whose performance was defined as extremely good or extremely poor by analysis of variance and correlation analysis. The results of principal component analysis descriminated the panelists with different scoring range more than different scoring trends depending on the treatments. Our study suggested combination of analysis of variance and correlation analysis provided valid basis for screening panelists.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.286-288
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• 2002

The rapid development of measurement systems for high power tests makes it possible to measure signals as well as analyze with the help of computer. Also, methods to evaluate such measurement systems are required recently. Uncertainty has been regarding as the most important factor in evaluating the measurement systems. Because of the character of the measurement systems for high power tests. the uncertainty shall be evaluated by each component. If the uncertainty evaluated by each component, it is convenient to evaluate total uncertainty of the measurement systems according to each component setting's combination. In this paper each component of high current measurement system of high power testing Dept. II in Korea Electrotechnology Research Institute is evaluated except sensors such as shunts and CTs. The total uncertainty of the measurement systems can be determined by that of each component including uncertainty of sensors.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.8
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• pp.780-785
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• 2010

The OPRoS (Open Platform for Robotic Services) framework is proposed as an application runtime environment for service robot systems. For the successful deployment of the OPRoS framework, fault tolerance support is crucial on top of its basic functionalities of lifecycle, thread and connection management. In the previous work [1] on OPRoS fault tolerance supports, we presented a framework-based fault tolerance architecture. In this paper, we extend the architecture with component-based fault tolerance techniques, which can provide more simplicity and efficiency than the pure framework-based approach. This argument is especially true for fault detection, since most faults and failure can be defined when the system cannot meet the requirement of the application functions. Specifically, the paper applies two widely-used fault detection techniques to the OPRoS framework: 'bridge component' and 'process model' component techniques for fault detection. The application details and performance of the proposed techniques are demonstrated by the same application scenario in [1]. The combination of component-based techniques with the framework-based architecture would improve the reliability of robot systems using the OPRoS framework.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1890-1901
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• 2022

We have assessed the applicability of the thermal-hydraulic system analysis code, SPACE, to a small modular reactor called SMART. For the assessment, the experimental data from a scale-down integral-test facility, SMART-ITL, were used. It was conformed that the SPACE code unrealistically calculates the safety injection flow rate through the CMT and SIT during a small-break loss-of-coolant experiment. This unrealistic behavior was due to the overprediction of interfacial heat transfer at the steam-water interface in a vertically stratified flow in the tanks. In this study, a special thermal-hydraulic component model has been developed to realistically calculate the interfacial heat transfer when a strong non-equilibrium two-phase flow is formed in the CMT or SIT. Additionally, we developed a special heat structure model, which analytically calculates the heat transfer from the hot steam to the cold tank wall. The combination of two models for the tank are called the special component model. We assessed it using the SMART-ITL passive safety injection system (PSIS) test data. The results showed that the special component model well predicts the transient behaviors of the CMT and SIT.

• Journal of Information Processing Systems
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• v.3 no.1
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• pp.33-37
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• 2007

Semantic clustering is important to various fields in the modem information society. In this work we applied the Independent Component Analysis method to the extraction of the features of latent concepts. We used verb and object noun information and formulated a concept as a linear combination of verbs. The proposed method is shown to be suitable for our framework and it performs better than a hierarchical clustering in latent semantic space for finding out invisible information from the data.

• The Journal of Information Technology
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• v.12 no.2
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• pp.31-37
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• 2009

Component-based software development [CBSD] is a new paradigm of recent software development. CBSD was started from reuse of software and study on software component technique. In order to improve produce and quality of software development, there is study on reuse of components lively and how to develop, share, and manage components effectively. In this study, I would like to suggest a method that is able to simply test a new application system by developing systems developed individually into components, registering them, and combining them.

• East Asian mathematical journal
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• v.5 no.1
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• pp.95-110
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• 1989

In a general variance component model, nonnegative quadratic estimators of the components of variance are considered which are invariant with respect to mean value translaion and have minimum bias (analogously to estimation theory of mean value parameters). Here the minimum is taken over an appropriate cone of positive semidefinite matrices, after having made a reduction by invariance. Among these estimators, which always exist the one of minimum norm is characterized. This characterization is achieved by systems of necessary and sufficient condition, and by a cone restricted pseudoinverse. In models where the decomposing covariance matrices span a commutative quadratic subspace, a representation of the considered estimator is derived that requires merely to solve an ordinary convex quadratic optimization problem. As an example, we present the two way nested classification random model. An unbiased estimator is derived for the mean squared error of any unbiased or biased estimator that is expressible as a linear combination of independent sums of squares. Further, it is shown that, for the classical balanced variance component models, this estimator is the best invariant unbiased estimator, for the variance of the ANOVA estimator and for the mean squared error of the nonnegative minimum biased estimator. As an example, the balanced two way nested classification model with ramdom effects if considered.