• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.747-752
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• 2008

Fiber-guided sensor system using a generator and a receiver can detect the amplitude of load or pressure. However, this type of sensor can show some difficulties in detecting the location of damages and pressure loadings. To overcome this weakness of this type, the ultrasonic active fiber sensor, which has an integrated ultrasonic generator and sensing part, was developed in this study. By using this sensor system, the location of mechanical loads can be exactly detected. Moreover, the ultrasonic active fiber sensor is more cost-effective than an ultrasonic fiber sensor using two piezoelectric transducers which are used as a generator and a receiver, respectively. Two applications of the ultrasonic active fiber sensor are demonstrated: cure monitoring of lead and measurement of liquid level. Present results showed that the active fiber sensor can be applied for various environmental sensing.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.5
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• pp.77-87
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• 2023

Wind turbines playing a critical role in renewable energy generation, accurately assessing their operational status is crucial for maximizing energy production and minimizing downtime. This study conducts a comparative analysis of different neural network models for wind turbine condition diagnosis, evaluating their effectiveness using a dataset containing sensor measurements and historical turbine data. The study utilized supervisory control and data acquisition data, collected from 2 MW doubly-fed induction generator-based wind turbine system (Model HQ2000), for the analysis. Various neural network models such as artificial neural network, long short-term memory, and recurrent neural network were built, considering factors like activation function and hidden layers. Symmetric mean absolute percentage error were used to evaluate the performance of the models. Based on the evaluation, conclusions were drawn regarding the relative effectiveness of the neural network models for wind turbine condition diagnosis. The research results guide model selection for wind turbine condition diagnosis, contributing to improved reliability and efficiency through advanced neural network-based techniques and identifying future research directions for further advancements.

• Journal of Gastric Cancer
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• v.7 no.4
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• pp.237-241
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• 2007

Purpose: Patients with hematologic diseases such as chronic myeloid leukemia (CML) or chronic lymphoid leukemia (CLL) are known to have an increased chance of acquiring a secondary neoplasm. Stomach cancer is one of the most common malignant diseases in Korea, and we investigated whether the incidence of secondary stomach cancer in patients with a hematologic disease increases, in order to determine if a more intensive screening program for detecting secondary gastric cancer was required. We also investigated the safety of performing a gastrectomy in hematologic disease patients. Materials and Methods: From 1992 to 2006, the medical records of 8376 patients diagnosed with one of the six common hematologic diseases were reviewed. Results: Nine secondary stomach cancers were found among the 8376 patients during the 15-year observation period. No surgical-related complications occurred, and there was no recurrence of stomach cancer if detected early. Conclusion: It seems that a more intensive screening program for detecting secondary gastric cancer in hematologic disease patients is not required, and surgery is not risky in these patients.

• Korean Journal of Clinical Laboratory Science
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• v.49 no.4
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• pp.420-426
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• 2017

Methicillin-resistant Staphylococcus (MRS) can be colonized in various body sites and is more frequently isolated in healthcare associated persons. This study aimed to evaluate the contamination rate of MRS in a high school environment, those living with closed life style. Staphylococcus aureus was isolated from only the hands of 2 students among a sample of 28 students, and S. aureus were susceptible to methicillin antibiotics. Coagulase negative Staphylococci (CoNS) were isolated from the hands of 26 students (26/28, 92.9%), and among them, 14 (53.8%) isolates were methicillin-resistant CoNS (MRCoNS). Among the 14 MRCoNS, S. warneri was the most common (8/14, 57%) and susceptible to most $non-{\beta}-lactam$ antibiotics, such as clindamycin, erythromycin, ciprofloxacin, tetracycline, gentamicin, and vancomycin. In a culture of 31 desks, S. aureus was not isolated but CoNS were isolated from 26 desks (26/31, 83.6%), which did not harbor the mecA gene. The other bacteria isolated from the hands and desks were Micrococcus and Bacillus spp. In conclusion, methicillin-resistant S. aureus was not isolated from the hands and desks of high school students. However, the frequency of MRCoNS harboring mecA gene were high in the hands of high school students. Therefore, to prevent and to control the transfer of infection, intensifying preventive education, such as hand washing, and active surveillance systems, such as an investigation of contamination or carrier rate of resistant bacteria are necessary.