• Journal of IKEEE
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• v.25 no.1
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• pp.212-217
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• 2021

Premature contraction arrhythmia is the most common disease among arrhythmia and it may cause serious situations such as ventricular fibrillation and ventricular tachycardia. Most of arrhythmia clasification methods have been developed with the primary objective of the high detection performance without taking into account the computational complexity. Also, personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. Therefore it is necessary to design efficient method that classifies arrhythmia by analyzing the persons's physical condition and decreases computational cost by accurately detecting minimal feature point based on only QRS features. We propose method for personalized specific classification of premature contraction arrhythmia based on QRS features in smart healthcare environments. For this purpose, we detected R wave through the preprocessing method and SOM and selected abnormal signal sets.. Also, we developed algorithm to classify premature contraction arrhythmia using QRS pattern, RR interval, threshold for amplitude of R wave. The performance of R wave detection, Premature ventricular contraction classification is evaluated by using of MIT-BIH arrhythmia database that included over 30 PVC(Premature Ventricular Contraction) and PAC(Premature Atrial Contraction). The achieved scores indicate the average of 98.24% in R wave detection and the rate of 97.31% in Premature ventricular contraction classification.

• Journal of Internet of Things and Convergence
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• v.9 no.1
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• pp.97-104
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• 2023

This paper is related to object segmentation using ESRGAN(Enhanced Super Resolution GAN) and SSS(Semantic Soft Segmentation). The segmentation performance of the object segmentation method using Mask R-CNN and SSS proposed by the research team in this paper is generally good, but the segmentation performance is poor when the size of the objects is relatively small. This paper is to solve these problems. The proposed method aims to improve segmentation performance of small objects by performing super-resolution through ESRGAN and then performing SSS when the size of an object detected through Mask R-CNN is below a certain threshold. According to the proposed method, it was confirmed that the segmentation characteristics of small-sized objects can be improved more effectively than the previous method.

• Steel and Composite Structures
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• v.42 no.1
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• pp.59-74
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• 2022

This study introduces a general reliability-based, performance-based design framework to design frames regarding their uncertainties and user-defined design goals. The Iterative-R method extracted from the main framework can designate a proper R (i.e., response modification factor) satisfying the design goal regarding target reliability index and pre-defined probability of collapse. The proposed methodology is based on FEMA P-695 and can be used for all systems that FEMA P-695 applies. To exemplify the method, multiple three-dimensional, four-story steel special moment-resisting frames are considered. Closed-form relationships are fitted between frames' responses and the modeling parameters. Those fits are used to construct limit state functions to apply reliability analysis methods for design safety assessment and the selection of proper R. The frameworks' unique feature is to consider arbitrarily defined probability density functions of frames' modeling parameters with an insignificant analysis burden. This characteristic enables the alteration in those parameters' distributions to meet the design goal. Furthermore, with sensitivity analysis, the most impactful parameters are identifiable for possible improvements to meet the design goal. In the studied examples, it is revealed that a proper R for frames with different levels of uncertainties could be significantly different from suggested values in design codes, alarming the importance of considering the stochastic behavior of elements' nonlinear behavior.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.460-462
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• 2021

Food basically must have nutrition and safety. Recently, a number of symptoms of food poisoning occurred in a kindergarten in Ansan, where food safety was suspected. Therefore, the safety of food is more demanding. In this paper, we propose a method to inprove the detector to secure food safety. The proposed method is to learn through the network of convolution neural network (CNN) and Faster region-CNN (Faster R-CNN) and test the images of normal and foreign products. As a result of testing through a deep learning model, the method that used Faster R-CNN in parallel with the existing foreign body detector algorithm showed better detection rate than other methods.

• Bulletin of the Korean Mathematical Society
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• v.49 no.2
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• pp.295-306
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• 2012

Let (R, $m_R$, k) be a local maximal commutative subalgebra of $M_n$(k) with nilpotent maximal ideal $m_R$. In this paper, we will construct a maximal commutative subalgebra $R^{ST}$ which is isomorphic to R and study some interesting properties related to $R^{ST}$. Moreover, we will introduce a method to construct an algebra in $MC_n$(k) with i($m_R$) = n and dim(R) = n.

• The Journal of the Korea Contents Association
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• v.10 no.8
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• pp.18-25
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• 2010

The study has proposed a method that simultaneously takes advantage of each projection matrix acquired by using column-directional two-dimensional PCA(C2DPCA) and row-directional two-dimensional LDA(R2DLDA). The proposed method can acquire a great secure recognition rate, with no relation to the number of training images, with acquired low-dimensional feature matrixes including both the horizontal and the vertical features of a face. Besides, in the alternate experiment of PCA and LDA to row-direction and column-direction respectively(C2DPCA & R2DLDA, C2DLDA & R2DPCA), we could make sure the system of 2 dimensional LDA with row-directional feature(C2DPCA & R2DLDA) obtain higher recognition rate with low dimension than opposite case. As a result of experimenting that, the proposed method has showed a greater recognition rate of 99.4% than the existing methods such as 2DPCA and 2DLDA, etc. Also, it was proved that its recognition processing is over three times as fast as that of 2DPCA or 2DLDA.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.101-108
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• 2017

As the quantum gate matrix is a $r^{n+1}{\times}r^{n+1}$ dimension when the radix is r, the number of control state vectors is n, and the number of target state vectors is one, the matrix dimension with increasing n is exponentially increasing. If the number of control state vectors is $2^n$, then the number of $2^n-1$ unit matrix operations preserves the output from the input, and only one can be performed the unitary operation to the target state vector. Therefore, this paper proposes a new method of function embedding that can replace $2^n-1$ times of unit matrix operations with deterministic contribution to matrix dimension by arithmetic power switch of the unitary gate. The proposed function embedding method uses a binary literal switch with a multivalued threshold, so that a general purpose hybrid MCU gate can be realized in a $r{\times}r$ unitary matrix.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.5
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• pp.631-640
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• 2013

This paper provides a comparison of the J-integral estimation method under combined primary and secondary stress in the R6, RCC-MR A16 code. The comparisons of each code are based on finite element analysis using ABAQUS with regard to the crack shape, crack depth, and magnitude of secondary load. The estimate of the R6 code is conservative near $L_r=1$, and that of the RCC-MR A16 code is conservative near $L_r=0$. As a result, this paper proposes a modified method of J-integral estimation in the R6, RCC_MR A16 code. The J-integral using the modified method corresponds to the finite element analysis result.

• Korean Journal of Organic Agriculture
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• v.14 no.2
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• pp.191-204
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• 2006

This study was conducted to identify the effect of planting date and cultivation method on soybean growth and yield in paddy field. The plant height of soybeans in single cropping(SC) was higher than those in cultivating after barley culture (CB). Considering planting date and cultivation method, plant height tend to be higher in SC with level row cultivation(LR) and in CB with high ridge cultivation(HR). In this SC method, nodule formation in LR was better than in HR, but number of nodules of cv. Hwangkeumkong was highest, regardless of planting date and cultivation method. In the progress of growth stage, leaf areas of all cultivars were distinctively increased in CB than in SC. However, dry weight of top plants and roots in SC was comparably higher than that in CB due to growing periods of the soybeans. In cultivation methods, general type of dry weight of top plants was higher in LR than in HR, however, root dry weight was via verses. Growth responses varied depending on cultivars, cultivation methods, and planting date and these factors affected to shoot root (T/R) ratio. The T/R ratios in LR and SC were higher than those in HR and CB. In R8 stage, number of pods and ripened seed varied depending on cultivars. cv. Hwaeomputkong, which showed early maturing trait, was lowest. However, both yield factors tended to be higher in HR and CB than in LR and SC. The ratios of ripened seeds percentage of cv. Hwangkeumkong and cv. Eunhakong were higher in CB than in SC. However, yields of cv. Daewonkon and cv. Taekwangkong were higher in CB than in SC.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.209-216
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• 2009

A development in method of evaluating the measurement precisions using approximate F tests and variance components from expected mean square (EMS) is investigated. The research proposes three-factor mixed measurement models with the fixed and random factors. Unrestricted and unconstrained design work was rarely studied, while restricted and constrained designs have been significantly discussed. The unrestricted and unconstrained designs assume to be an independence of interaction. The proposed evaluation method about the measurement precisions can be extended to four-factor random measurement model or mixed measurement model. The study also presents the three evaluation indexes of precisions such as R&RTR (Reproducibility & Repeatability-To-Total Precision Ratio), PTR (Precision-To-Tolerance Ratio), and SNR (Signal-To-Noise Ratio). Numerical examples are proposed to evaluate the approximate F tests with Satterthwaite degrees of freedom and three indexes using the measurement precisions from EMS.