• Journal of Biomedical Engineering Research
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• v.14 no.4
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• pp.341-348
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• 1993

Automated system to analyze liver function test results is presented based on fuzzy logic knowledge. Clinician's knowledge and experience was first expressed in linguistic terms fol- lowed by conversion to numerical values to create membership functions of disease possibility for each test item and liver disease. Membership functions were then compensated for different relative importances of test items. Liver diseases considered were acute viral hepatitis (AVH), chronic persistent hepatitis(CPH), chronic active hepatitis(CAH), and liver cirrhosis(LC), Liver function test results of alanine aminotransferase(ALT), aspartate amino- transferase(AST) , glutamate dehydrogenase(GDH), ornithine carbamyltransferase(OCT) , ALT/AST, and 10* GDH/ALT in 218 patients were analyzed by the present system, welch resulted in 80% accuracy. AVH and CAH showed the highest 93 % and the lowest 58% ac- curacies, respectively, which was similar to the clinician's expectation. The simple mathemat- ical formulation of the present system would enable an easy implementation in commercial analysis instruments. Also, the identical fuzzy logic can be applied to similar diagnostic envi- ronments in general.

• Proceedings of the KSR Conference
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• 2002.10a
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• pp.202-207
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• 2002

The rubber type AGT system is operated by driverless that signaling is CBTC type. The system function is acomplished exactly to obtain the safety and reliability of system and the system is designed to minimize risk. In order to design the system, the functional analysis is performed. Recently functional analysis is performed by RDD-100 which is used and verified by aerospace, military, etc. Therefore, The design tool RDD-100 is used to perform functional analysis in AGT system development project.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.286-288
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• 1996

To make correct prognoses in the area of orthodontics, dentists use cephalometric analysis methods. Currently, most of them involve two main steps: initial diagnosis and treatment establishment. Currently, dentists work manually on X-ray film to measure the cephalogmetric parameters. The work is tedious and time-consuming, and sometimes produces incorrect results. We developed an automated cephalometric analysis system, in which dentists can easily locate reference points needed for the analysis and get the results almost at the same time.

• Journal of Korean Society for Quality Management
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• v.48 no.3
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• pp.381-393
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• 2020

Purpose: The purpose of this study was to find useful solutions by analyzing causes and results about defects on mechanical drawing notes and provide an automated tool with solutions to mechanical engineers. Methods: The collected data for defects on mechanical drawing notes were from ongoing development and mass production projects. Various measurement methods were used based on the Lean 6 Sigma analysis such as Process analysis, C&E diagram and some statistical analysis. Results: The results of this study are as follows; The results of the Lean 6 Sigma analysis, the validity of the selected indicators for improving drawing notes quality was verified through the verification of cause variables. The strategy established to improve the mechanical drawing notes was reflected as an automated program, and the defects were within a manageable range and achieved target Sigma level. Conclusion: Through the application of the "Mechanical drawing notes automation tool", it is expected to resolve the "Voice of Customer, VOC" and "Voice of Business, VOB".

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.6
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• pp.77-91
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• 2023

Recently, there has been a worldwide increase in research and development on automated vehicles for commercialization. It is expected that the use of level 3 autonomous vehicles on continuous-flow roads will be introduced and will increase. Consequently, various studies have been conducted to investigate the impact of mixed traffic flow with automated vehicles based on the market penetration rate (MPR). However, these studies have been conducted independently, and the results have shown different trends. Therefore, this study attempted a quantitative analysis of the impact of automated vehicles on mixed traffic flow on uninterrupted roads through a meta-analysis. The results showed that the effect size estimated from an MPR of 75% or higher was statistically significant.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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• pp.68-74
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• 2003

Modem automated manufacturing processes employ automated guided vehicles(AGVs) for material handling, which serve several machining centers(MCs) in a factory. Optimal scheduling of AGVs can significantly help to increase the efficiency of the manufacturing process by minimizing the idle time of MCs waiting for the raw materials. In this paper, we will analyse the requirements for an optimal schedule and then provide a mathematical framework for an efficient schedule of material delivery by an AGV. With this model, the optimal number of MCs to be utilized will also be determined. Finally, the material delivery schedule employing multiple journeys to the MCs by the AGV will be carried out. Through rigorous analysis and simulation experiments, we shall show that such a delivery strategy will optimize the overall performance.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.57-60
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• 2012

In this paper, we have performed a safety analysis on an automotive evaporator inspection system. We performed the bi-directional analysis on the manufacturing line. Software Fault Tree Analysis (SFTA) as backward analysis and Software Failure Modes, Effects, & Criticality Analysis (SFMECA) as forward analysis are performed alternately to detect potential cause-to-effect relations. The analysis results indicate the possibility of searching and summarizing fault patterns for future reusability.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.spc1
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• pp.243-249
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• 2004

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.288-291
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• 2008

Recently, the importance and necessity of engineering analysis has shown a steady growth. However, researchers working in small and medium enterprises know little about the usefulness of engineering analysis and suffer from lack of technical knowledge. Axial fan is air fluid machinery in various fields of industry such as automobile, electric appliance, and heavy machinery. It is also a time and budget consuming equipment to develop the axial fan through physical experiments. In order to overcome this problem, we have designed and developed a web-base automated simulator for axial fan's fluid analysis using supercomputer. Automated simulator means that all of processes for engineering analysis including pre-process, solving, and post-process can be performed automatically without user intervention after transferring fan model(CAD files) made by user. After executing the simulator with some parameters, user can receive the report including pressure P and flow rate Q. In this paper, we introduce the architecture of our easy and efficient automated engineering analysis simulator, related techniques and result of development.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.705-713
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• 2006

For the analysis of multiunit extracellular neural signals as multiple spike trains, neural spike sorting is essential. Existing algorithms for the spike sorting have been unsatisfactory when the signal-to-noise ratio(SNR) is low, especially for implementation of fully-automated systems. We present a novel method that shows satisfactory performance even under low SNR, and compare its performance with a recent method based on principal component analysis(PCA) and fuzzy c-means(FCM) clustering algorithm. Our system consists of a spike detector that shows high performance under low SNR, a feature extractor that utilizes projection pursuit based on negentropy maximization, and an unsupervised classifier based on Gaussian mixture model. It is shown that the proposed feature extractor gives better performance compared to the PCA, and the proposed combination of spike detector, feature extraction, and unsupervised classification yields much better performance than the PCA-FCM, in that the realization of fully-automated unsupervised spike sorting becomes more feasible.