• Journal of Oriental Neuropsychiatry
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• v.30 no.4
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• pp.327-340
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• 2019

Objectives: Alzheimer's disease (AD) is a complex disease accompanied by slow impairment of memory and coordination leading to behavioral changes. To date, the only treatment option is to delay the progress of the disease. The purpose of this study was to investigate the synergistic effects of combination treatment with donepezil and three herbal extracts SIP-3 in the AD mouse model induced by amyloid-β (Aβ). Methods: We tested SIP-3 extracts for the cytotoxicity on Aβ-treated SH-SY5Y cells. Then the synergistic effects of SIP-3 and donepezil were evaluated in the AD mouse model using animal experiments and the next generation sequencing (NGS) study. Results: We found that co-treatment with SIP-3 extracts and donepezil increased the viability in Aβ-treated SH-SY5Y cells. The beneficial effects of the co-treatment were also observed in the Aβ-induced AD mouse model. The NGS study was performed to show that the co-treatment of SIP-3 and donepezil restored the disease phenotype closely to the normal level in the AD mouse model in terms of mRNA expression. However, the phenotypes were only partially restored. Conclusions: This study suggests that the combination treatment has a potential to be used for the treatment of AD. However, longer periods of treatment may be required.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.28B no.10
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• pp.831-841
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• 1991

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

• Water Engineering Research
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• v.5 no.2
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• pp.101-109
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• 2004

Aggregating information by combining forecasts from two or more forecasting methods is an alternative to using forecasts from just a single method to improve forecast accuracy. This paper describes the development and use of a monthly inflow forecast model based on an optimal linear combination (OLC) of forecasts derived from naive, persistence, and Ensemble Streamflow Prediction (ESP) forecasts. Using the cross-validation technique, the OLC model made 1-month ahead probabilistic forecasts for the Chungju multi-purpose dam inflows for 15 years. For most of the verification months, the skill associated with the OLC forecast was superior to those drawn from the individual forecast techniques. Therefore this study demonstrates that OLC can improve the accuracy of the ESP forecast, especially during the dry season. This study also examined the value of the OLC forecasts in reservoir operations. Stochastic Dynamic Programming (SDP) derived the optimal operating policy for the Chungju multi-purpose dam operation and the derived policy was simulated using the 15-year observed inflows. The simulation results showed the SDP model that updated its probability from the new OLC forecast provided more efficient operation decisions than the conventional SDP model.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.2
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• pp.61-68
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• 2020

E-sports has grown steadily in recent years and has become a popular sport in the world. In this paper, we propose a win-loss prediction model of League of Legends at the start of the game. In League of Legends, the combination of a champion statistics of the team that is made through each player's selection affects the win-loss of the game. The proposed model is a deep learning model based on Bidirectional LSTM embedding which considers a combination of champion statistics for each team without any domain knowledge. Compared with other prediction models, the highest prediction accuracy of 58.07% was evaluated in the proposed model considering a combination of champion statistics for each team.

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.233-238
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• 2010

In this paper, we propose a multiple classifier combination method based on image degradation modeling to improve recognition performance on low-quality images. Using an image degradation model, it generates a set of classifiers each of which is specialized for a specific image quality. In recognition, it combines the results of the recognizers by weighted averaging to decide the final result. At this time, the weight of each recognizer is dynamically decided from the estimated quality of the input image. It assigns large weight to the recognizer specialized to the estimated quality of the input image, but small weight to other recognizers. As the result, it can effectively adapt to image quality variation. Moreover, being a multiple-classifier system, it shows more reliable performance then the single-classifier system on low-quality images. In the experiment, the proposed multiple-classifier combination method achieved higher recognition rate than multiple-classifier combination systems not considering the image quality or single classifier systems considering the image quality.

• Korean Journal of Acupuncture
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• v.35 no.4
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• pp.187-202
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• 2018

Objectives : Non-invasive transcranial electrical stimulation is one of therapeutic interventions to change in neural excitability of the cortex. Transcranial electro-acupuncture (TEA) can modulate brain functions through changes in cortical excitability as a model of non-invasive transcranial electrical stimulation. Some composites of fermented Scutellaria baicalenis (FSB) can activate intercellular signaling pathways for activation of brain-derived neurotrophic factor that is critical for formation of neural plasticity in stroke patients. This study was aimed at evaluation of combinatory treatment of TEA and FSB on behavior recovery and cortical neural excitability in rodent focal stroke model. Methods : Focal ischemic stroke was induced by photothrombotic injury to the motor cortex of adult rats. Application of TEA with 20 Hz and $200{\mu}A$ in combination with daily oral treatment of FBS was given to stroke animals for 3 weeks. Motor recovery was evaluated by rotating bean test and ladder working test. Electrical activity of cortical pyramidal neurons of stroke model was evaluated by using multi-channel extracellular recording technique and thallium autometallography. Results : Compared with control stroke group who did not receive any treatment, Combination of TEA and FSB treatment resulted in more rapid recovery of forelimb movement following focal stroke. This combination treatment also elicited increase in spontaneous firing rate of putative pyramidal neurons. Furthermore expression of metabolic marker for neural excitability was upregulated in peri-infract area under thallium autometallography. Conclusions : These results suggest that combination treatment of TEA and FSB can be a possible remedy for motor recovery in focal stroke.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.1
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• pp.70-74
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• 1997

Data on 2,571 lactation records of Nili-Ravi buffaloes from four institutional herds and four field recording centers were analyzed under an animal model to see the effect of season definition on the error variance of the fitted model. Herd-year-season(HYS) was the main fixed effect along with permanent environment, breeding value and residuals as the random effects. All known relationships among the animals were considered. The error variance differed for various HYS combinations. It was minimum when then months were not grouped into seasons. The four or Five season scenarios were better than the two season scenarios. The average number of lactations represented in a HYS combination varied widely from 6 to 28. Very few subclasses for a given HYS combination warrants the use of fewer seasons for animal model evaluation of buffaloes.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.500-504
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• 2008

The objective of this paper is to evaluate the feasibility of using an optimization model as a effective way to search conjunctive operation scheme to meet two conditions; one is to minimize the electric cost for pumping and another is to meet the water demand for satisfying customers. The feasibility is confirmed as comparing the best combinations of pumps between multi-regional water supply networks from multiple sources which are obtained through an optimization modeling and EPAnet modeling. KModsim model, a network optimization model, was used to determine conjunctive operation scheme in the pipe system. KModsim, based on Lagrangian Relaxation algorithm, is useful for modeling network system and obtaining simultaneously pump combination and water allocation with given input option such as energy unit cost supplying from a source into a consumer, operating pumping combination. This study develops the procedure of determining optimal conjunctive operation scheme with using KModsim model. As a study region, the water supplying systems of the Geojae-city in the Geongsang Namdo Province was selected and investigated. The EPAnet hydraulic simulation result(Ryu et al, 2007, KSWW) gave input data for optimization model; energy unit price(won/$m^3$), water service available area etc.. It was assured that the combination of pump operation through optimum conjunctive operation is to be optimum scheme to obtain the best economic water allocation with comparison to the hydraulic simulation result such as electric cost and pump combination cases. The results obtained through the study are as follows. First, It was found that a well-allocated water supply scheme, the best combination of pump operation through optimum joint operation, promises to save the electric cost and satisfy all operational goals such as stability and revenues during the period. Second, an application of KModSim, a network model, gave the amount of water allocation from each source to a consumer with consideration of economic supply. Finally, in a service area available to supply through conjunctive operation of existing inter-regional water supply networks within short distance, a conjunctive operation is useful for determining each transmission pipeline's service area and maximizing the effectiveness of optimizations in pumping operation time.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.84-98
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• 1995

Network-based model were developed to predict short term future traffic volume based on current traffic, historical average, and upstream traffic. It is presumed that upstream traffic volume can be used to predict the downstream traffic in a specific time period. Three models were developed for traffic flow prediction; a combination of historical average and upstream traffic, a combination of current traffic and upstream traffic, and a combination of all three variables. The three models were evaluated using regression analysis. The third model is found to provide the best prediction for the analyzed data. In order to balance the variables appropriately according to the present traffic condition, a heuristic adaptive weighting system is devised based on the relationships between the beginning period of prediction and the previous periods. The developed models were applied to 15-minute freeway data obtained by regular induction loop detectors. The prediction models were shown to be capable of producing reliable and accurate forecasts under congested traffic condition. The prediction systems perform better in the 15-minute range than in the ranges of 30-to 45-minute. It is also found that the combined models usually produce more consistent forecasts than the historical average.

• Proceedings of the SAREK Conference
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• 2005.11a
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• pp.281-287
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• 2005

This study investigates the pressure drop and heat transfer characteristics of heat exchanger according to the combination of fin configuration and fin pitch of each row by the similitude experiments with the finned-tube geometry scaled as large as four times Finned-tube heat exchanger has 2 rows, and fin geometry consists of two cases, louver-louver and louver-slit. Fin pitch is varied with three types in each case, 6-6 mm, 8-8 mm and 8-6 mm. Results show that total heat transfer can be occurred evenly at each row by varying the fin pitch of 1st row and 2nd row. Heat transfer rate and pressure drop characteristics change according to the combination for fin geometry and fin pitch.