• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.223-230
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• 2002

In a speech coding system using excitation source of voiced and unvoiced, it would be involves a distortion of speech waveform in case coexist with a voiced and an unvoiced consonants in a frame. This paper present a new method of TSIUVC (Transition Segment Including Unvoiced Consonant) approximate-synthesis by using Least Mean Square. The TSIUVC extraction is based on a zero crossing rate and IPP (Individual Pitch Pulses) extraction algorithm using residual signal of FIR-STREAK Digital Filter. As a result, This method obtain a high Quality approximation-synthesis waveform by using Least Mean Square. The important thing is that the frequency signals in a maximum error signal can be made with low distortion approximation-synthesis waveform. This method has the capability of being applied to a new speech coding of Voiced/Silence/TSIUVC, speech analysis and speech synthesis.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.1
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• pp.73-78
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• 2008

A polarimetric fiber-optic CT has been developed by using a sensing coil made of a length of sun fiber. A Faraday rotator mirror is attached to the end of the sensor coil to double the sensitivity and to suppress the residual linear birefringence effect. From the current measurements, the linear error no more than ${\pm}2[%]$ was obtained. The output of spun fiber sensor coil was compared with those of the twisted- and the flint glass fiber's, and it fumed out to almost 50 times, 2 times more sensitive, respectively.

• Journal of the Ergonomics Society of Korea
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• v.29 no.6
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• pp.861-868
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• 2010

This study explored an extended three-dimensional Fitts' law that is more suited for the pointing task than the conventional Fitts' law. The experiments were conducted under the manipulation of the distance to the target, size of the target, and direction of the target's location that can be described by two angles, $\theta1$ and $\theta2$. Considering the starting point as the center of coordinates, $\theta1$ is the angle between the positive z-axis and the target location and $\theta2$ is the angle between the positive y-axis and the projected target location on the x-y plane. From the experimental results, we confirmed that all four variables significantly affect the movement time. As we extended the index of difficulty of the conventional Fitts' model by incorporating $\theta1$ and $\theta2$, we established an extended Fitts' model that showed better accordance with the empirical data than the conventional Fitts' model and 3D Fitts' law of Murata and Iwase, in terms of the $r^2$ and the standard error of the residual between the measured movement time and the predicted value.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.15 no.2
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• Journal of the Korea Society of Computer and Information
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• v.23 no.4
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• pp.147-153
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• 2018

In this paper, we propose an efficient WBC 14-Diff classification which performs using the WBC-ResNet-152, a type of CNN model. The main point of view is to use Super-pixel for the segmentation of the image of WBC, and to use ResNet for the classification of WBC. A total of 136,164 blood image samples (224x224) were grouped for image segmentation, training, training verification, and final test performance analysis. Image segmentation using super-pixels have different number of images for each classes, so weighted average was applied and therefore image segmentation error was low at 7.23%. Using the training data-set for training 50 times, and using soft-max classifier, TPR average of 80.3% for the training set of 8,827 images was achieved. Based on this, using verification data-set of 21,437 images, 14-Diff classification TPR average of normal WBCs were at 93.4% and TPR average of abnormal WBCs were at 83.3%. The result and methodology of this research demonstrates the usefulness of artificial intelligence technology in the blood cell image classification field. WBC-ResNet-152 based morphology approach is shown to be meaningful and worthwhile method. And based on stored medical data, in-depth diagnosis and early detection of curable diseases is expected to improve the quality of treatment.

• Journal of Korean Academy of Nursing
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• v.48 no.5
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• pp.588-600
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• 2018

Purpose: The purpose of this study was to test a model of nursing competencies of nursing simulation learners. The conceptual model was based on the theory of Jeffries's simulaton theory. Methods: Data collection was conducted in October 2017 for 310 students from two nursing universities in Kyungbuk area for 20 days. Data analysis methods were covariance structure analysis using SPSS 21.0 and AMOS 22.0 statistical programs. Results: The hypothetical model was a good fit for the data. The model fit indices were comparative fit index=.97, normed fit index=.94, Tucker-Lewis Index=.97, root mean square error of approximation=.44, and standardized root mean square residual=.04. Teacher factors were directly related to simulation design characteristics, and it was confirmed that the curriculum, classroom operation and teaching method of the instructors were important factors. Learner factors were found to have a direct effect on nursing competence, self-confidence, and clinical performance that belong to nursing capacity. In particular, the results of this study indicate that the simulation design characteristics have a partial mediating effect on learner factors and clinical performance, and a complete mediating effect on learner factors and clinical judgment ability. Conclusion: In order to improve the learner's clinical performance and clinical judgment ability, it is necessary to conduct practical training through nursing simulation besides preparing the learner and the educator.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.137-145
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• 2020

Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.

• Journal of Magnetics
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• v.21 no.2
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• pp.209-214
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• 2016

This paper analyzes the magnetic property according to the machined shape of steel material with non-oriented silicon steel (50PN470/50A470), that is most commonly used in the design of electrical equipment. Toward this end, specimens were produced and divided into Bar-Specimen (Epstein Frame Tester) and Ring-Specimen (Toroidal Ring Tester). The characteristics of the electrical Silicon steel were measured using the instruments solely dedicated to measuring each specimen. The core loss of the Bar-Specimen, which is commonly used, was found to be less than that of the Ring-Specimen. This is a very important design factor in achieving the objectives of improving the product efficiency and predicting the performance of electrical equipment. It serves as a critical point of view in order to reduce the error between design value and product value. A comparative analysis was conducted regarding various characteristics (Hysteresis, B-H characteristic, Iron loss, Minor loop, Coercive force, Residual magnetic flux density, etc.) of the electrical silicon steel considered in the design of the electrical equipment according to the specimen.

• International Journal of Reliability and Applications
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• v.3 no.1
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• pp.1-16
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• 2002

In reliability engineering, the bathtub-shaped hazard rates play an important role in survival analysis and many other applications as well. For the bathtub-shaped, initially the hazard rate decreases from a relatively high value due to manufacturing defects or infant mortality to a relatively stable middle useful life value and then slowly increases with the onset of old age or wear out. In this paper, we present a new two-parameter lifetime distribution function, called the Loglog distribution, with Vtub-shaped hazard rate function. We illustrate the usefulness of the new Vtub-shaped hazard rate function by evaluating the reliability of several helicopter parts based on the data obtained in the maintenance malfunction information reporting system database collected from October 1995 to September 1999. We develop the S-Plus add-in software tool, called Reliability and Safety Assessment (RSA), to calculate reliability measures include mean time to failure, mean residual function, and confidence Intervals of the two helicopter critical parts. We use the mean squared error to compare relative goodness of fit test of the distribution models include normal, lognormal, and Weibull within the two data sets. This research indicates that the result of the new Vtub-shaped hazard rate function is worth the extra function-complexity for a better relative fit. More application in broader validation of this conclusion is needed using other data sets for reliability modeling in a general industrial setting.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.263-269
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• 2016

The purpose of this study is to challenge a computational regression-type problem, that is handling large-size data, in which conventional metamodeling techniques often fail in a practical sense. To solve such problems, regression-type boosting, one of ensemble model techniques, together with bootstrapping-based re-sampling is a reasonable choice. This study suggests weight updates by the amount of the residual itself and a new error decision criterion which constructs an ensemble model of models selectively chosen by rejection limits. Through these ideas, we propose AdaBoost.RMU.R as a metamodeling technique suitable for handling large-size data. To assess the performance of the proposed method in comparison to some existing methods, we used 6 mathematical problems. For each problem, we computed the average and the standard deviation of residuals between real response values and predicted response values. Results revealed that the average and the standard deviation of AdaBoost.RMU.R were improved than those of other algorithms.