• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1151-1160
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• 2014

In DNA microarray studies, the number of genes far exceeds the number of samples and the gene expression measures are highly correlated. Partial least squares regression (PLSR) is one of the popular methods for dimensional reduction and known to be useful for the classifications of microarray data by several studies. In this study, we suggest a modified version of the partial least squares regression to analyze gene expression data with survival information. The method is designed as a new gene selection method using PLSR with an iterative procedure of imputing censored survival time. Mean square error of prediction criterion is used to determine the dimension of the model. To visualize the data, plot for variables superimposed with samples are used. The method is applied to two microarray data sets, both containing survival time. The results show that the proposed method works well for interpreting gene expression microarray data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.862-864
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• 2003

Thresholding is a popular image segmentation method that converts a gray-level image into a binary image. The selection of optimum threshold has remained a challenge over decades. Many image segmentation techniques are developed using information about image in other space rather than the image space itself. Most of the technique based on histogram analysis information-theoretic approaches. In this paper, the criterion function for finding optimal threshold is developed using an intensity-based classuncertainty (a histogram-based property of an image) and region-homogeneity (an image morphology-based property). The theory of the optimum thresholding method is based on postulates that objects manifest themselves with fuzzy boundaries in any digital image acquired by an imaging device. The performance of the proposed method is illustrated on experimental data obtained by W-band millimeter-wave radiometer image under different noise level.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.61-68
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• 2019

Spatial modulation (SM) is the first proposed space modulation technique. By further utilizing the quadrature spatial dimension, quadrature spatial modulation (QSM) has been developed as an amendment to SM system to enhance the overall spectral efficiency. Both techniques are capable of entirely eliminating interchannel interference (ICI) at the receiver. In this paper, we propose a simple adaptive hybrid switching transmission scheme to obtain better system performance than SM and QSM systems under a fixed transmission date rate. The presented modulator selection criterion for switching between spatial modulator and quadrature spatial modulator is based on the larger received minimum distance of spatial modulator and quadrature spatial modulator to exploit the spatial channel freedom. It is shown through Monte Carlo simulations that the proposed hybrid SM and QSM switching system yields lower error performance than the conventional SM and QSM systems under the same fixed data rate and thus can provide signal to noise ratio (SNR) gain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5287-5303
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• 2018

Handling vast amount of data found in large transactional datasets is an obvious challenge for the conventional data mining algorithms. Addressing this challenge, our paper proposes a parallel approach for proper decomposition of mining problem into sub-problems in order to find frequent patterns from these datasets. The proposed, Pattern Mining for Large Distributed Dataset (PMLDD) approach, ensures minimum dependencies as well as minimum communications among sub-problems. It establishes a linear aggregation of the intermediate results so that it can be adapted to large-scale programming models like MapReduce. In this context, an algorithmic structure for MapReduce programming model is presented. PMLDD guarantees an efficient load balancing among the sub-problems by a specific selection criterion. Further, it optimizes the number of required iterations over the dataset for mining frequent patterns as compared to the existing approaches. Finally, we believe that our approach is scalable enough to handle larger datasets in terms of performance evaluation, and the result analysis justifies all these mentioned concerns.

• Communications for Statistical Applications and Methods
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• v.28 no.3
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• pp.281-294
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• 2021

In this paper, we propose an adaptive regression method based on the single-layer neural network structure. We adopt a symmetric activation function as units of the structure. The activation function has a flexibility of its form with a parametrization and has a localizing property that is useful to improve the quality of estimation. In order to provide a spatially adaptive estimator, we regularize coefficients of the activation functions via ℓ₁-penalization, through which the activation functions to be regarded as unnecessary are removed. In implementation, an efficient coordinate descent algorithm is applied for the proposed estimator. To obtain the stable results of estimation, we present an initialization scheme suited for our structure. Model selection procedure based on the Akaike information criterion is described. The simulation results show that the proposed estimator performs favorably in relation to existing methods and recovers the local structure of the underlying function based on the sample.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.1
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• pp.59-65
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• 2022

Virtual memory is used as the method to ensure the safety of the system through memory protection in the real-time system. TLB miss caused by using virtual memory makes the real-time system WCET more pessimistically. TLB lockdown can be applied as a method to improve this problem. However, processors with limited TLB lockdown entries, a selection criterion is needed to efficiently utilize the TLB lockdown entry. In this paper, the most frequently accessed virtual pages in the process are applied to the TLB lockdown by analyzing memory profiling. The results showed that micro data TLB miss stall cycle and main data TLB miss stall cycle of the processor decreased by at least 4.7% and up to 29.7%.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.4_1
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• pp.505-511
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• 2022

The objective of this article is finding optimized locations of active mounts applied to 6-DOF beam structure with two active paths. When sinusoidal excitation forces are applied to the beam structure, secondary forces from two active mounts which can minimize (ideally becoming zero) transmitted forces are calculated mathematically and the vibration attenuation performance is validated through computer simulations. When the force applied to two active mounts are relatively low, those specific locations are considered as optimized location of active mounting system. As the location of mount changes, amplitude and phase of secondary forces in each path are analyzed with 3D plots. Based on the simulation results, a criterion for selecting mounting location is suggested and it would be very useful for selecting actuators for active mounts appropriately.

• Computers and Concrete
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• v.30 no.5
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• pp.357-367
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• 2022

In this paper, we propose an efficient control method that can be transformed into a general building control problem for building structure control using these reliability criteria. To facilitate the calculation of controller H∞, an efficient solution method based on Linear Matrix Inequality (LMI) is introduced, namely H∞-based LMI control. In addition, a self-tuning predictive grey fuzzy controller is proposed to solve the problem caused by wrong parameter selection to eliminates the effect of dynamic coupling between degrees of freedom (DOF) in Self-Tuning Fuzzy Controllers. We prove stability using Lyapunov's stability theorem. To check the applicability of the proposed method, the proposed controller is applied and the control characteristics are determined. The simulation assumes system uncertainty in the controller design and emphasizes the use of acceleration feedback as a practical consideration. Simulation results show that the performance of the proposed controller is impressive, stable, and consistent with the performance of LMI-based methods. Therefore, an effective control method is suitable for seismic reinforcement of civil buildings.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4478-4488
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• 2015

This paper aims to develop and validate a situational judgement test to diagnose the Competencey of public ethics for undergraduates. A criterion group composing of high performers was formed. Critical incidents and responses were developed from interviews with members of the criterion group. Also an expert committee was composed of six university members who have professional knowledge and experience on Competencey based selection or education. This committee reviewed all the items developed and selected some of them for the final test. Item validity and reliability were examined through the final test that 519 college students took. The result of the confirmatory as well as exploratory factor analysis showed that the Competencey of public ethics consisted of 2 sub-elements which were work ethics and democratic citizenship. The correlation between results of the test and the HEXACO model was statistically significant. Overall, the findings of the study highlight that a situational judgement test can be developed and utilized to diagnose Competencey levels of public ethics for undergraduates.

• Safety and Health at Work
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• v.7 no.4
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• pp.322-325
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• 2016

Background: Musculoskeletal disorders (MSDs) are a common problem among carpet weavers. This study was undertaken to introduce affecting personal and occupational factors in developing the number of MSDs among carpet weavers. Methods: A cross-sectional study was performed among 862 weavers in seven towns with regard to workhouse location in urban or rural regions. Data were collected by using questionnaires that contain personal, workplace, and information tools and the modified Nordic MSDs questionnaire. Statistical analysis was performed by applying Poisson and negative binomial mixed models using a full Bayesian hierarchical approach. The deviance information criterion was used for comparison between models and model selection. Results: The majority of weavers (72%) were female and carpet weaving was the main job of 85.2% of workers. The negative binomial mixed model with lowest deviance information criterion was selected as the best model. The criteria showed the convergence of chains. Based on 95% Bayesian credible interval, the main job and weaving type variables statistically affected the number of MSDs, but variables age, sex, weaving comb, work experience, and carpet weaving looms were not significant. Conclusion: According to the results of this study, it can be concluded that occupational factors are associated with the number of MSDs developing among carpet weavers. Thus, using standard tools and decreasing hours of work per day can reduce frequency of MSDs among carpet weavers.