• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.06a
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• pp.1-18
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• 2000

This paper describes firstly a prediction for desirable features of the machine tool in the year 2015 and beyond, and then delineates something definite in relation to some representative machine tools, which could be realised in very near future. The paper depicts furthermore another aspect of future machine tools, I. e., innovative structural designs. In addition, author asserts the importance of grass root-like knowledge, when predicting the desirable feature of machine tools future together with showing some evidences.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.79-80
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• 2012

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.437-451
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• 2023

Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

• Korea Journal of Hospital Management
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• v.4 no.2
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• pp.354-368
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• 1999

This research aims to compare between regression and neural network in terms of the predictive ability of the overhead costs in hospitals. For this purpose, this research uses the number of out-patients and complex medical treatments as explaining variables. Thirty-one hospitals were used for the empirical test The test result shows that the regression model has a more predictive ability than the neural network.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.30A no.1
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• pp.73-85
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• 1993

This paper presents a design and implementation of CAD(Computer-Aided Design) system with tools and design environments for IC(Intergrated Circuits)design. The CAD system can be easily installed in various sites with limited resources, since most CAD tools and design environments are available in the public-domain and Unix & X Window-based PC-386 and Workstation is used for the hardware platform. In order to improve the flexibility of the CAD system, objects are defined in the context of tools and environments` and object tables are programmed to describe the integration of CAD tools and design environments. During the execution, tool-objects deal with intertool communication and round-robin mechanism to incrementally control the execution of CAD tools. The IC design of LPC(Linear Predictive Coding) Speech Synthesizer is carried out to find out improvements and bugs of the CAD system.

• Korean Journal of Adult Nursing
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• v.27 no.1
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• pp.29-38
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• 2015

Purpose: The purpose of the study was to validate fall risk assessment scales among hospitalized adult patients in South Korea using the electronic medical records by comparing sensitivity, specificity, positive predictive values, and negative predictive values of Morse Fall Scale (MFS), Bobath Memorial Hospital Fall Risk Assessment Scale (BMFRAS), and Johns Hopkins Hospital Fall Risk Assessment tool (JHFRAT). Methods: A total of 120 patients who experienced fall episodes during their hospitalization from June 2010 to December 2013 was categorized into the fall group. Another 120 patients, who didn't experience fall episodes with age, sex, clinical departments, and the type of wards matched with the fall group, were categorized to the comparison group. Data were analyzed for the comparisons of sensitivity, specificity, positive and negative predictive values, and the area under the curve of the three tools. Results: MFS at a cut-off score of 48 had .806 for ROC curves, 76.7% for sensitivity, 77.5% for specificity, 77.3% for positive predictive value, and 76.9% for negative predictive value, which were the highest values among the three fall assessment scales. Conclusion: The MFS with the highest score and the highest discrimination was evaluated to be suitable and reasonable for predicting falls of inpatients in med-surg units of university hospitals.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.5
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• pp.417-425
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• 2003

H.264, which is the latest video coding standard of both ITU-T(International Telecommunication Union-Telecommunication standardization sector) and MPEG(Moving Picture Experts Group), adopts new video coding tools such as variable block size motion estimation, multiple reference frames, quarter-pel motion estimation/compensation(ME/MC), 4${\times}$4 Integer DCT(Discrete Cosine Transform), and Rate-Distortion Optimization, etc. These new video coding tools provide good coding of efficiency compared with existing video coding standards as H.263, MPEG-4, etc. However, these new coding tools require the increase of encoder complexity. Therefore, in order to apply H.264 to many real applications, fast algorithms are required for H.264 coding tools. In this paper, when encoder MacroBlock(MB) mode is decided by rate-distortion optimization tool, fast mode decision algorithm by skipping variable block size ME/MC and spatial-predictive coding, which occupies most encoder complexity, is proposed. In terms of computational complexity, the proposed method runs about 4 times as far as JM(Joint Model) 42 encoder of H.264, while the PSNR(peak signal-to-noise ratio)s of the decoded images are maintained.

• PNF and Movement
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• v.16 no.3
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• pp.495-503
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• 2018

Purpose: This study analyzes the predictive power of upper extremity activity and the activities of daily living in patients with stroke using an easy-to-use evaluation tool. Methods: The Fugl-Meyer assessment (FMA) of the upper extremity and action research arm test (ARAT) are performed, and the Korean modified Barthel index (K-MBI) is measured. The predictive power of the upper extremity activity level and the daily activity level are analyzed using regression analysis. The statistical significance level is 0.05. Results: The coefficient of determination, R2, for predicting the ARAT using FMA was high at 0.88, but the regression equation for predicting the K-MBI using the FMA and ARAT did not show a statistically significant difference. Conclusion: The assessment of the upper extremity should be performed at the activity level, as well as the impairment level. The assessment for predicting the activities of daily living should be carried out for each level of the international classification of functioning (ICF), disability, and health, which can be linked to daily life, in addition to the assessment of the upper arm. Future research should conduct more diverse analyses using the ICF assessment tools at various levels.

• Molecules and Cells
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• v.46 no.1
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• pp.21-32
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• 2023

MicroRNAs (miRNAs) play cardinal roles in regulating biological pathways and processes, resulting in significant physiological effects. To understand the complex regulatory network of miRNAs, previous studies have utilized massivescale datasets of miRNA targeting and attempted to computationally predict the functional targets of miRNAs. Many miRNA target prediction tools have been developed and are widely used by scientists from various fields of biology and medicine. Most of these tools consider seed pairing between miRNAs and their mRNA targets and additionally consider other determinants to improve prediction accuracy. However, these tools exhibit limited prediction accuracy and high false positive rates. The utilization of additional determinants, such as RNA modifications and RNA-binding protein binding sites, may further improve miRNA target prediction. In this review, we discuss the determinants of functional miRNA targeting that are currently used in miRNA target prediction and the potentially predictive but unappreciated determinants that may improve prediction accuracy.

• Tribology and Lubricants
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• v.36 no.4
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• pp.215-231
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• 2020

The paper presents extensive survey and review of experimental and analytical researches on fluid film bearings and squeeze film dampers (SFDs) for turbomachinery available in open literature (major archival international journals) published recently (2018 and 2019 only). Over 60 published research works are reviewed based on the research topics and objectives, the types of bearings, size of bearings, and main design parameters with a brief summary of experiments and/or predictions in each work. Some important findings and general observations about the experimental and/or predictive data are also presented. There are several major trends observed throughout the survey. A large portion of the papers focuses on bearing surface textures and effect of operating and assembly conditions on static and/or dynamic forced performances, as well as bearing surface roughness and wear patterns. Researches on geometry of orifices and recesses in hydrostatic (or hybrid) bearings, as well as bearing system stability predictions using thermohydrodynamic analysis and computational fluid dynamics (CFD), are considered as significant topics. Studies on SFDs mainly focus on experimental identification of force coefficients for various SFD geometries and sealing conditions. Reliable experiments of fluid film bearings and SFDs along with the development of experimentally benchmarked predictive tools enable reinforcement of the path for reliable implementations of the bearing components into high performance rotating machinery operating at extreme and harsh conditions. The extensive list of sources of recent experiments in the available open literature is a welcome addition to the analytical community to gauge the accuracy of predictive tools.