• The Journal of Korean Obstetrics and Gynecology
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• v.20 no.3
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• pp.200-212
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• 2007

Purpose: To find objective validity of minimal acupuncture using a modified guide tube as a method to verify the effect of acupuncture. Methods: Subjects of this study were participants of a randomized clinical trial which was practiced to verify the effect of acupuncture on postmenopausal hot flash. There were 2 arms of treatment, one's for active acupuncture group(AG) with manipulation and De qi, the other's for minimal acupuncture group(MG) using a modified guide tube which was designed to give minimal stimulation to the patient. After 8 weeks' treatment followed by 4 weeks' observation, participants were asked to fill in self-report forms on their education, previous experiences of acupuncture, original idea on the efficacy of acupuncture and recognition of blinding. Results: 19 participants of 26 in AG and 19 of 26 in MG completed the self-report form. There was no difference between AG and MG in their education(p=0.5976, Fisher exact test) and previous experiences of acupuncture(p=0.9999, Fisher exact test). In their original ideas on the efficacy of acupuncture, most of AG and MG respondents have been thought that acupuncture is very effective or quite effective, and there was no difference between 2 groups(p=0.5065). 16 of 19 in AG and 14 of 19 in MG believed that they underwent more effective way, there was no statistical difference between 2 groups(p=0.6928, Fisher exact test). Participants believed in undergoing more effective way not because they recognized treatment method, but they were satisfied with the effectiveness of treatment retrospectively. Conclusion: As the result of this study, these authors suggest that minimal acupuncture using a modified guide tube is acceptable as a method to verify the effect of acupuncture in acupuncture-familiar Korean culture. Also further studies on the stimulation-specific effect of minimal acupuncture are demanded.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.83-93
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• 2017

A typical approach to visualizing k (${\geq}2$)-group multidimensional data is to use Fisher's canonical discriminant analysis (CDA). CDA finds the best low-dimensional subspace that accommodates k group centroids in the Mahalanobis space. This paper proposes an alternative visualization procedure functioning in the Euclidean space, which finds the primary dimension with maximum discrimination of k group centroids and the secondary dimension with maximum dispersion of all observational units. This hybrid procedure is especially useful when the number of groups k is two.

• Management Science and Financial Engineering
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• v.16 no.3
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• pp.21-47
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• 2010

Quantity discounts provide a practical foundation for supply chain inventory policies, improving the supplier's profit and reducing the buyer's inventory cost simultaneously. Traditional quantity-discount research, which deals with inventory coordination between a buyer and a supplier, is extended to a stationary stochastic environment. This research shows that the magnitude of the optimal discounts scheduled by the deterministic quantity discount models may not be large enough to cover the buyer's additional inventory stocking risks under uncertain conditions. As a result, the buyer's total inventory cost may often increase rather than decrease. In contrast, the proposed model allows the supplier to identify the discount level, which shares the buyer's amplified risk associated with temporary overstocking and ensures that both buyer and supplier benefit economically. The performance of the proposed model was tested in the continuous review environments via numerical experiments. The experimental results support the proposed method as a feasible alternative in coordinating inventory decisions under stochastic demand.

• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.27-33
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• 2012

The Ethernet Passive Optical Network (EPON) has been considered to be one of the most promising solutions for the implementation of the Fiber To The Home (FTTH) technology designed to ameliorate the "last mile" bandwidth bottleneck. In the EPON network, an efficient and fair bandwidth allocation is a very important issue, since multiple optical network units (ONUs) share a common upstream channel for packet transmission. To increase bandwidth utilization, an EPON system must provide a way to adaptively allocate the upstream bandwidth among multiple ONUs in accordance to their bandwidth demands and requirements. We present a new hybrid method that satisfies these requirements. The advantage of our method comes from the consideration of application-specific bandwidth allocation and the minimization of the idle bandwidth. Our simulation results show that our proposed method outperforms existing dynamic bandwidth allocation methods in terms of bandwidth utilization.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.330-338
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• 2017

The purpose of this study is to examine the effect of blended learning approach on academic achievement and self directed learning skills of nursing undergraduate students. This experimental study is designed for a nonequivalent control group. The number of subjects in this research consists of 145, where 75 of the experimental group participated in blended learning program and 70 of the control group didn't do. The data was analyzed by $x^2$-test, Fisher's exact test, t-test and paired t-test. The effects of blended learning approach on learning outcomes in women's health nursing are as follows : The academic achievement of the experimental group has been more elevated than that of the control group on final examination. The experimental group has made increase in self directed learning skills. The blended learning approach on learning outcomes in nursing major are effective. This study has significant implication in that it identified the availability of the blended learning program and that it would be a useful teaching and learning method to achieve learning outcomes.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.170-177
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• 2014

This paper presents a new method of classification of the induction machine faults using Time Frequency Representation, Particle Swarm Optimization and artificial neural network. The essence of the feature extraction is to project from faulty machine to a low size signal time-frequency representation (TFR), which is deliberately designed for maximizing the separability between classes, a distinct TFR is designed for each class. The feature vectors size is optimized using Particle Swarm Optimization method (PSO). The classifier is designed using an artificial neural network. This method allows an accurate classification independently of load level. The introduction of the PSO in the classification procedure has given good results using the reduced size of the feature vectors obtained by the optimization process. These results are validated on a 5.5-kW induction motor test bench.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.59-74
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• 2004

The paper considers the Bayesian interval estimation for the common mean of several normal populations. A Bayesian procedure is proposed based on the idea of matching asymptotically the coverage probabilities of Bayesian credible intervals with their frequentist counterparts. Several frequentist procedures based on pivots and P-values are introduced and compared with Bayesian procedure through simulation study. Both simulation results demonstrate that the Bayesian procedure performs as well or better than any available frequentist procedure even from a frequentist perspective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.11
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• pp.44-55
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• 2019

This study was undertaken to examine changes in the performance of nurses before and after initial cardiac arrest, and compare the performance, confidence, and satisfaction between two groups: group 1, Rapid Cycle Deliberate Practice simulation method; group 2, traditional simulation method. The participants were 122 nurses (group 1: 62, group 2: 60). Data were collected from March 18 to 29, 2019 and analyzed using the SPSS Version 23.0 program, by applying descriptive statistics, Fisher's exact test, t-test, Wilcoxon sign rank test, and Mann-Whitney U-test. Comparing the educational effects of the traditional simulation training vs. RCDP simulation training, some items of performance were significantly different (z=-2.02, p=0.044 / z=-2.42, p=0.015 / z=-3.03, p=0.002), but no difference was observed in the levels of confidence (z=0.388, p=0.699) and satisfaction (t=0.72, p=0.476) between the two groups. This study confirms that both training methods are effective teaching modules for enhancing the nurse's ability to perform resuscitation with confidence. Hence, we suggest applying the appropriate simulation method, according to the subjects included during education, and contents in the training of Advanced Life Support for nurses. Effectiveness of the modules can be ascertained by applying the RCDP simulation training method in various fields.

• Steel and Composite Structures
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• v.19 no.4
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• pp.953-966
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• 2015

Carbonation depth was verified in 40 points of two 57 years old concrete viaducts. Field testing (phenolphthalein spraying) was performed on the structures. Data obtained were statistically analyzed by the Kolmogrov-Smirnov's test, one-way analysis of variance (ANOVA's test), and Fisher's method. The results revealed significant differences between maximum carbonation depths of different elements of the same concrete structure. Significant differences were also found in the carbonation of different concrete structures inserted in the same macroclimate. Microclimatic factors such as temperature and local humidity, sunshine, wind, wetting and drying cycles, among others, may have been responsible by the behavior of carbonation in concrete.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.33-39
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• 2004

In this paper. we design the learning algorithm of LVQ which is used Forward Counter Propagation Networks to improve classification performance of LVQ networks. The weights of Forward Counter Propagation Networks which is between input layer and cluster layer can be learned to determine initial reference vectors by using SOM algorithm and to learn reference vectors by using LVQ algorithm. Finally. pattern vectors is classified into subclasses by neurons which is being in the cluster layer, and the weights of Forward Counter Propagation Networks which is between cluster layer and output layer is learned to classify the classified subclass, which is enclosed a class. Also. kr the number of classes is determined, the number of neurons which is being in the input layer, cluster layer and output layer can be determined. To prove the performance of the proposed learning algorithm. the simulation is performed by using training vectors and test vectors that ate Fisher's Iris data, and classification performance of the proposed learning method is compared with ones of the conventional LVQ, and it was a confirmation that the proposed learning method is more successful classification than the conventional classification.