• Smart Structures and Systems
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• v.6 no.3
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• pp.335-347
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• 2010

Recent advances in hardware and instrumentation technology have allowed the possibility of deploying very large sensor arrays on structures. Exploiting the huge amount of data that can result in order to perform vibration-based structural health monitoring (SHM) is not a trivial task and requires research into a number of specific problems. In terms of pressing problems of interest, this paper discusses: the design and optimisation of appropriate sensor networks, efficient data reduction techniques, efficient and automated feature extraction methods, reliable methods to deal with environmental and operational variability, efficient training of machine learning techniques and multi-scale approaches for dealing with very local damage. The paper is a result of the ESF-S3T Eurocores project "Smart Sensing For Structural Health Monitoring" (S3HM) in which a consortium of academic partners from across Europe are attempting to address issues in the design of automated vibration-based SHM systems for structures.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.284-287
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• 1987

In this paper, the design and implementation of a multiprocessor based Die Bonder Machine for the semiconductor will be described. This the partial research result, that is, the 1st year portion of the project to be performed for a period of two years from June, 1986 to May, 1988. The mechanical system consists of the following three subsystems : (i) transfer head unit, (ii) die feeding XY-table unit, and (iii) plunge up unit. The overall control system is designed to be essentially a master-slave type in which each slave is functionally fixed in view of software and also the time shared common bus structure with hardwired bus arbitration scheme is utilized, the control system consists of the following three subsystems each of which employs a 16 bits microprocessor MC 68000 : (i) die bonder processor controller, (ii) visual recognition/inspection and display system, (iii) the servo control system. It is reported that the proposed control system were applied to Working Sample and tested in real system, and the results are successful as a working sample phase.

• Journal of Biomedical Engineering Research
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• v.44 no.1
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• pp.25-32
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• 2023

Recognizing the size and location of prostate cancer is critical for prostate cancer diagnosis, treatment, and predicting prognosis. This paper proposes a model to classify the tumor region and normal tissue with cross-sectional visual images of prostatectomy tissue. We used specimen images of 44 prostate cancer patients who received prostatectomy at Gachon University Gil Hospital. A total of 289 prostate slice images consist of 200 slices including tumor region and 89 slices not including tumor region. Images were divided based on the presence or absence of tumor, and a total of 93 features from each slice image were extracted using Radiomics: 18 first order, 24 GLCM, 16 GLRLM, 16 GLSZM, 5 NGTDM, and 14 GLDM. We compared feature selection techniques such as LASSO, ANOVA, SFS, Ridge and RF, LR, SVM classifiers for the model's high performances. We evaluated the model's performance with AUC of the ROC curve. The results showed that the combination of feature selection techniques LASSO, Ridge, and classifier RF could be best with an AUC of 0.99±0.005.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.4
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• pp.80-88
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• 1997

An experimental investigation of the fatigue through crack growth behavior under simple stepped variable loading condition has been performed using Al7075-T651. Experiments were carried out by using cantilever bending type specimens, with chevron notches on a small electro-magnetic test machine. Tensile overloads have a retarding effect on the fatigue crack growth rates, therefore tensile overloads were used for the beneficial effect on the fatigue life. While in most cases compressive overloads have only a vanishing effect on crack growth rates, some experiments with single edge crack tension specimens reveal a marked growth retardation. The stress ratios used in this investigations varies from R=0.32 to 0.81, from R=0.04 to 0.76, from R=-0.15 to 0.73, and from R=-0.33 to 0.68 and the peak load for each case was not varied. The crack growth and crack closure were measured by Kikukawa's compliance method with a strain gauge mounted on the backside of each specimens. The results obtained are as follows. When the stepped variable load was applied, the smaller the stress ration was, the larger the delayed retardation of the crack growth rate was. The fatigue crack growh rate data obtained for through cracks were plotted well against the effective stress intensity factor range from 4.0 to 20.0MP{a^{SQRT}m}. It was found that the effective stress intensity factor range ratio was related well to the opening stress intensity factor, the maximum stress intensity factor, and crack length.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.15 no.5
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• pp.65-71
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• 2006

This paper presents the robust design of gripper part for a high-speed LCD(Liquid Crystal Display) transfer system. In this paper, the $1^{st}$ DOE(Design of Experiment) is conducted to find out main-effect factors for the design of gripper part. Thirty-six analysis are performed using $ANSYS^{(R)}$ and their results are statistically analyzed using $MINITAB^{(R)}$, which shows that the factors, i.e., First-width, Second-width, Rec-width, and thickness of gripper part, are more important than other factors. The main effect plots shows that the maximum deflection and mass of gripper part are minimized by increasing First-width, Second-width, Rec-width and thickness. The $2^{nd}$ DOE is conducted to obtain RSM(Response Surface Method) equation. The CCD(Central Composite Design) technique with four factors is used. Optimum design is conducted using the RSM equation. Genetic algorithm is used for optimal design. Six sigma robust design is conducted to find out a guideline for control range of design parameter. To obtain six sigma level quality, the standard deviations of design parameters are shown to be controlled within 5% of average design value.

• Genomics & Informatics
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• v.5 no.3
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• pp.102-106
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• 2007

Radiofrequency (RF) radiation at the frequency of mobile phones has been not reported to induce cellular responses in in vitro and in vivo models. We exposed HEI-OC1, conditionally-immortalized mouse auditory cells, to RF radiation to characterize cellular responses to 1763 MHz RF radiation. While we could not detect any differences upon RF exposure, whole-genome expression profiling might provide the most sensitive method to find the molecular responses to RF radiation. HEI-OC1 cells were exposed to 1763 MHz RF radiation at an average specific absorption rate (SAR) of 20 W/kg for 24 hr and harvested after 5 hr of recovery (R5), alongside sham-exposed samples (S5). From the whole-genome profiles of mouse neurons, we selected 9 differentially-expressed genes between the S5 and R5 groups using information gain-based recursive feature elimination procedure. Based on support vector machine (SVM), we designed a prediction model using the 9 genes to discriminate the two groups. Our prediction model could predict the target class without any error. From these results, we developed a prediction model using biomarkers to determine the RF radiation exposure in mouse auditory cells with perfect accuracy, which may need validation in in vivo RF-exposure models.

• Journal of IKEEE
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• v.26 no.3
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• pp.488-493
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• 2022

In manufacturing sites, bearing fault in eletrically driven motors cause the entire system to shut down. Stopping the operation of this environment causes huge losses in time and money. The reason of this bearing defects can be various factors such as wear due to continuous contact of rotating elements, excessive load addition, and operating environment. In this paper, a motor driving environment is created which is similar to the domestic manufacturing sites. In addition, based on the established environment, we propose a dataset for bearing fault detection by collecting changes in vibration characteristics that vary depending on normal and defective conditions. The sensor used to collect the vibration characteristics is Microphone G.R.A.S. 40PH-10. We used various machine learning models to build a prototype bearing fault detection system trained on the proposed dataset. As the result, based on the deep neural network model, it shows high accuracy performance of 92.3% in the time domain and 98.3% in the frequency domain.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.19-27
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• 2022

In this study, we propose a language and platform to describe and manage the MLOps(Machine Learning Operations) workflow for time series data anomaly detection. Time series data is collected in many fields, such as IoT sensors, system performance indicators, and user access. In addition, it is used in many applications such as system monitoring and anomaly detection. In order to perform prediction and anomaly detection of time series data, the MLOps platform that can quickly and flexibly apply the analyzed model to the production environment is required. Thus, we developed Python-based AI/ML Modeling Language (AMML) to easily configure and execute MLOps workflows. Python is widely used in data analysis. The proposed MLOps platform can extract and preprocess time series data from various data sources (R-DB, NoSql DB, Log File, etc.) using AMML and predict it through a deep learning model. To verify the applicability of AMML, the workflow for generating a transformer oil temperature prediction deep learning model was configured with AMML and it was confirmed that the training was performed normally.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.83-89
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• 2005

Molding shrinkage is one of the problems to be solved in conventional injection molding. Despite many trying-out has been to solve it, intrinsic cause of shrinkage such as orientation and thermal exchange between melt and mold has not been solved yet. For reducing shrinkage and residual stress on molding, injection compression molding process was invented. In this study, experiments about effects of injection compression molding's parameters on shrinkage of PMMA molding were conducted and compared with conventional injection molding's shrinkage. Before the injection compression molding experiment, molding shrinkage rate was predicted by analyzing pvT diagram and was compared with the results of experiment. The shrinkage rate of injection compression molding was lower than convention injection molding's one which was different from the predicted shrinkage. The reason was observed that the experimental mold was not a proper type for injection compression, flowing backward of melt into nozzle and unreasonable mechanism of injection molding machine.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.105-114
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• 2001

Modulus of elasticity, modulus of rigidity, damping ratio, and natural frequency of three varieties of boxthorn (Lycium chinense Mill) (Cheongyang #2, Cheongyang gugija, and Cheongyang native) branches were analyzed. Modulus of elasticity and modulus of elasticity and modulus of rigidity of the boxthorn branch was determined using standard formula after simple beam bending and torsion test, respectively, using an universal testing machine. Damping ratio and natural frequency of branches were determined using a system consisted of an accelerometer, a PC equipped with A/D converter, and a software for data analysis. Relationship between the elastic modulus and branch diameter in overall varieties and branch types showed a good correlation (r -0.81). There was, however, no correlation between torsional rigidity and branch diameter. The internal damping results were highly variable and the overall range of the damping ratio of the boxthorn branch was 0.014-0.087, which indicated that the branch was a lightly damped structure. The natural frequency of the boxthorn branch was in the range of 89-363 rad/s for the overall varieties and branch types. A good correlation (r 0.82) existed between the natural frequency and branch diameter in overall varieties and branch type.