• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.401-410
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• 2021

Popular in discriminant classification analysis, k-nearest neighbor classification methods have limitations that do not reflect the local characteristic of the data, considering only the number of fixed neighbors. Considering the local structure of the data, the adaptive nearest neighbor method has been developed to select the number of neighbors. In the analysis of high-dimensional data, it is common to perform dimension reduction such as random projection techniques before using k-nearest neighbor classification. Recently, an ensemble technique has been developed that carefully combines the results of such random classifiers and makes final assignments by voting. In this paper, we propose a novel discriminant classification technique that combines adaptive nearest neighbor methods with random projection ensemble techniques for analysis on high-dimensional data. Through simulation and real-world data analyses, we confirm that the proposed method outperforms in terms of classification accuracy compared to the previously developed methods.

• The Korean Journal of Pain
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• v.34 no.3
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• pp.271-287
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• 2021

Background: Postoperative pain management is crucial for patients undergoing total knee arthroplasty (TKA). There have been many recent clinical trials on post-TKA peripheral nerve block; however, they have reported inconsistent findings. In this meta-analysis, we aimed to comprehensively analyze studies on post-TKA analgesia to provide evidence-based clinical suggestions. Methods: We performed a computer-based query of PubMed, Embase, the Cochrane Library, and the Web of Science to retrieve related articles using neurothe following search terms: nerve block, nerve blockade, chemodenervation, chemical neurolysis, peridural block, epidural anesthesia, extradural anesthesia, total knee arthroplasty, total knee replacement, partial knee replacement, and others. After quality evaluation and data extraction, we analyzed the complications, visual analogue scale (VAS) score, patient satisfaction, perioperative opioid dosage, and rehabilitation indices. Evidence was rated using the Grading of Recommendations Assessment, Development, and Evaluation approach. Results: We included 16 randomized controlled trials involving 981 patients (511 receiving peripheral nerve block and 470 receiving epidural block) in the final analysis. Compared with an epidural block, a peripheral nerve block significantly reduced complications. There were no significant between-group differences in the postoperative VAS score, patient satisfaction, perioperative opioid dosage, and rehabilitation indices. Conclusions: Our findings demonstrate that the peripheral nerve block is superior to the epidural block in reducing complications without compromising the analgesic effect and patient satisfaction. Therefore, a peripheral nerve block is a safe and effective postoperative analgesic method with encouraging clinical prospects.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.4
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• pp.191-197
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• 2021

To calculate the induced charge of atoms in molecular dynamics, linear equations for the induced charges need to be solved. As induced charges are determined at each time step, the process involves considerable computational costs. Hence, an efficient method for calculating the induced charge distribution is required when analyzing large systems. This paper introduces the Uzawa method for solving saddle point problems, which occur in linear systems, for the solution of the Lagrange equation with constraints. We apply the accelerated Uzawa algorithm, which reduces computational costs noticeably using the Schur complement and preconditioned conjugate gradient methods, in order to overcome the drawback of the Uzawa parameter, which affects the convergence speed, and increase the efficiency of the matrix operation. Numerical models of molecular dynamics in which two gold nanoparticles are placed under external electric fields reveal that the proposed method provides improved results in terms of both convergence and efficiency. The computational cost was reduced by approximately 1/10 compared to that for the Gaussian elimination method, and fast convergence of the conjugate gradient, as compared to the basic Uzawa method, was verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1904-1913
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• 2021

With the proliferation of smart phones and the development of IoT technology, it has become possible to collect personal data for public purposes. However, users are afraid of voluntarily providing their private data due to privacy issues. To remedy this problem, mainly three techniques have been studied: data disturbance, traditional encryption, and homomorphic encryption. In this work, we perform simulations to compare them in terms of accuracy, message length, and computation delay. Experiment results show that the data disturbance method is fast and inaccurate while the traditional encryption method is accurate and slow. Similar to traditional encryption algorithms, the homomorphic encryption algorithm is relatively effective in privacy preserving because it allows computing encrypted data without decryption, but it requires high computation costs as well. However, its main cost, arithmetic operations, can be processed in parallel. Also, data analysis using the homomorphic encryption needs to do decryption only once at any number of data.

• Steel and Composite Structures
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• v.44 no.1
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• pp.81-89
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• 2022

The purposes of the present work it to study the effect of shear deformation on the static post-buckling response of simply supported functionally graded (FGM) axisymmetric beams based on classical, first-order, and higher-order shear deformation theories. The behavior of postbuckling is introduced based on geometric nonlinearity. The material properties of functionally graded materials (FGM) are assumed to be graded in the thickness direction according to a simple power law distribution in terms of the volume fractions of the constituents. The equations of motion and the boundary conditions derived using Hamilton's principle. This article compares and addresses the efficiency, the applicability, and the limits of classical models, higher order models (CLT, FSDT, and HSDT) for the static post-buckling response of an asymmetrically simply supported FGM beam. The amplitude of the static post-buckling obtained a solving the nonlinear governing equations. The results showing the variation of the maximum post-buckling amplitude with the applied axial load presented, for different theory and different parameters of material and geometry. In conclusion: The shear effect found to have a significant contribution to the post-buckling behaviors of axisymmetric beams. As well as the classical beam theory CBT, underestimate the shear effect compared to higher order shear deformation theories HSDT.

• Korean Journal of Schizophrenia Research
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• v.22 no.2
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• pp.34-41
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• 2019

Objectives: This study was performed to examine the effects of the public attention to 'crime of schizophrenia' on the use of mental health services in patients with schizophrenia using big data analysis. Methods: Data on the frequency of internet searches for 'crime of schizophrenia' and the patterns of mental health service utilization by patients with schizophrenia spectrum disorders by month were collected from Naver big data and the Health Insurance Review and Assessment Services in Korea, respectively. Their correlations in the same and following month for lagged effect were examined. Results: The number of outpatients correlated negatively with public attention to 'crime of schizophrenia' in the same month. The lagged relationship between public attention and the number of admissions in psychiatric wards was also found. In terms of sex differences, the use of outpatient services among female patients correlated negatively with public attention in the same month while the number of male patients' admissions in both same and following month correlated positively with public attention. Conclusion: These findings suggested that public attention to 'crime of schizophrenia' could negatively affect illness behavior in patients with schizophrenia.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.251-258
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• 2018

In mathematics and computer science, an optimization problem is the problem of finding the best solution from feasible ones. In the context of genetic algorithm, the difficulty of an optimization problem can be explained in terms of problem epistasis. In biology, epistasis means that the phenotype of a gene is suppressed by one or more genes, but in an evolutionary algorithm it means the interaction between genes. In this paper, we experimentally show that problem epistasis and the performance of genetic algorithm are closely related. We compared problem epistasis (One-Max, Royal Road, and NK-Landscape) using a framework that quantifies problem epistasis based on Shannon's information theory, and could show that problem becomes more difficult as problem epistasis grows. In the case that a genetic algorithm finds the optimal solution, performance is compared through the number of generations, otherwise through the ratio of the fitness of the optimal solution to that of the best solution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1586-1591
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• 2022

Kirchhoff-Love plate (KLP) equation is a well established theory for a description of a deformation of a thin plate under certain outer source. Meanwhile, analysis of a vibrating plate in a frequency domain is important in terms of obtaining the main frequency/eigenfunctions and predicting the vibration of plate. Among various modal analysis methods, dynamic mode decomposition (DMD) is one of the efficient data-driven methods. In this work, we carry out DMD based modal analysis for KLP where thin plate is under effects of sine-type outer force. We first construct discrete time series of KLP solutions based on a finite difference method (FDM). Over 720,000 number of FDM-generated solutions, we select only 500 number of solutions for the DMD implementation. We report the resulting DMD-modes for KLP. Also, we show how DMD can be used to predict KLP solutions in an efficient way.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.170-185
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• 2023

The advent of big data has brought about the need for analytics. Natural language processing (NLP), a field of big data, has received a lot of attention. Topic modeling among NLP is widely applied to identify key topics in various academic journals. The Korean Society of Industrial and Systems Engineering (KSIE) has published academic journals since 1978. To enhance its status, it is imperative to recognize the diversity of research domains. We have already discovered eight major research topics for papers published by KSIE from 1978 to 1999. As a follow-up study, we aim to identify major topics of research papers published in KSIE from 2000 to 2022. We performed topic modeling on 1,742 research papers during this period by using LDA and BERTopic which has recently attracted attention. BERTopic outperformed LDA by providing a set of coherent topic keywords that can effectively distinguish 36 topics found out this study. In terms of visualization techniques, pyLDAvis presented better two-dimensional scatter plots for the intertopic distance map than BERTopic. However, BERTopic provided much more diverse visualization methods to explore the relevance of 36 topics. BERTopic was also able to classify hot and cold topics by presenting 'topic over time' graphs that can identify topic trends over time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.10
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• pp.2643-2657
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• 2023

Scene graphs are structured representations that can clearly convey objects and the relationships between them, but are often heavily biased due to the highly skewed, long-tailed relational labeling in the dataset. Indeed, the visual world itself and its descriptions are biased. Therefore, Unbiased Scene Graph Generation (USGG) prefers to train models to eliminate long-tail effects as much as possible, rather than altering the dataset directly. To this end, we propose Geometric and Semantic Improvement (GSI) for USGG to mitigate this issue. First, to fully exploit the feature information in the images, geometric dimension and semantic dimension enhancement modules are designed. The geometric module is designed from the perspective that the position information between neighboring object pairs will affect each other, which can improve the recall rate of the overall relationship in the dataset. The semantic module further processes the embedded word vector, which can enhance the acquisition of semantic information. Then, to improve the recall rate of the tail data, the Class Balanced Seesaw Loss (CBSLoss) is designed for the tail data. The recall rate of the prediction is improved by penalizing the body or tail relations that are judged incorrectly in the dataset. The experimental findings demonstrate that the GSI method performs better than mainstream models in terms of the mean Recall@K (mR@K) metric in three tasks. The long-tailed imbalance in the Visual Genome 150 (VG150) dataset is addressed better using the GSI method than by most of the existing methods.