• Journal of the Korean Society for Precision Engineering
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• v.15 no.3
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• pp.50-60
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• 1998

This paper is concerned with the design of two residual control charts for real-time monitoring of the continuous flow processes. Two different control charts are designed under the situation that observations are correlated each other. Kalman-Filter based model estimation is employed when the process model is known. A black-box approach, based on Back-Propagation Neural Network, is also applied for the design of control chart when there is no prior information of process model. Performance of the designed control charts and traditional control charts is evaluated. Average run length(ARL) is adopted as a criterion for comparison. Experimental results show that the designed control chart using the Neural Network's modeling has shorter ARL than that of the other control charts when process mean is shifted. This means that the designed control chart detects the out-of-control state of the process faster than the others. The designed control chart using the Kalman-Filter based model estimation also has better performance than traditional control chart when process is out-of-control state.

• Nuclear Engineering and Technology
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• v.36 no.5
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• pp.475-484
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• 2004

Extending the lifetime of a nuclear power plant [(hereafter referred to simply as NPP)] is one of the most important concerns in the global nuclear industry. Cables are one of the long-life items that have not been considered for replacement during the design life of a NPP. To extend the cable life beyond the design life, it is first necessary to prove that the design life is too conservative compared with actual aging. Condition monitoring is useful means of evaluating the aging condition of cable. In order to simulate natural aging in a nuclear power plant. a study on accelerated aging must first be conducted. In this paper, evaluations of mechanical aging degradation for a neoprene cable jacket were performed after accelerated aging under tcontinuous and intermittent heating conditions. Contrary to general expectations, intermittent heating to the neoprene cable jacket showed low aging degradation, 50% break-elongation, and 60% indenter modulus, compared with continuous heating. With a plant maintenance period of 1 month after every 12 or 18 months operation, we can easily deduce that the life time of the cable jacket of neoprene can be extended much longer than extimated through the general EQ test. which adopts continuous accelerated aging for determining cable life. Therefore, a systematic approach that considers the actual environment conditions of the nuclear power plant is required for determining cable life.

• Journal of Computing Science and Engineering
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• v.2 no.2
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• pp.180-199
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• 2008

Technology has had a tremendous impact on our daily lives. Recently, technology and its impact on aging has become an expanding field of inquiry. A major reason for this interest is that the use of technology can help older people who experience deteriorating health to live independently. In this paper we give a brief review of the in-home monitoring technologies for the elderly. In the pilot study, we analyze the possibility of employing the data generated by a continuous, unobtrusive nursing home monitoring system for predicting elevated(abnormal)pulse pressure(PP) in elderly(PP=systolic blood pressure-diastolic blood pressure). Our sensor data capture external information(behavioral) about the resident that is subsequently reflected in the predicted PP. By continuously predicting the possibility of elevated pulse pressure we may alert the nursing staff when some predefined threshold is exceeded. This approach may provide additional blood pressure monitoring for the elderly persons susceptible to blood pressure variations during the time between two nursing visits. We conducted a retrospective pilot study on two residents of the TigerPlace aging in place facility with age over 70, that had blood pressure measured between 100 and 300 times during a period of two years. The pilot study suggested that abnormal pulse pressure can be reasonably well estimated (an area under ROC curve of about 0.75) using apartment bed and motion sensors.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.1-15
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• 2017

Installation of sensors networks for continuous in-service monitoring of structures and their efficiency conditions is a current research trend of paramount interest. On-line monitoring systems could be strategically useful for road infrastructures, which are expected to perform efficiently and be self-diagnostic, also in emergency scenarios. This work researches damage detection in composite concrete-steel structures that are typical for highway overpasses and bridges. The techniques herein proposed assume that typical damage in the deck occurs in form of delamination and cracking, and that it affects the peak power spectral density of dynamic curvature. The investigation is performed by combining results of measurements collected by long-gauge fiber optic strain sensors installed on monitored structure and a statistic approach. A finite element model has been also prepared and validated for deepening peculiar aspects of the investigation and the availability of the method. The proposed method for real time applications is able to detect a documented unusual behavior (e.g., damage or deterioration) through long-gauge fiber optic strain sensors measurements and a probabilistic study of the dynamic curvature power spectral density.

• Journal of the Korea institute for structural maintenance and inspection
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• v.6 no.2
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• pp.145-155
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• 2002

It is essential for health monitoring of a cable-stayed bridge to provide more accurate and enough information from the sensors. In experimental modal testing, the chosen measurement locations and the number of measurements have a major influence on the quality of the results. The choice is often difficult for complex structures like a cable-stayed bridge. It is extremely important a cable-stayed bridge to minimize the number of sensing operations required to monitor the structural system. In order to obtain the desired accuracy for the structural test, several issues must take into consideration. Two important issues are the number and location of response sensors. There are usually several alternative locations where different sensors can be located. On the other hand, the number of sensors might be limited due to economic constraints. Therefore, techniques such as methodologies, algorithms etc., which address the issue of limited instrumentation and its effects on resolution and accuracy in health monitoring systems are paramount to a damage diagnosis approach. This paper discusses an optimum sensor placement criterion suitable to the identification of structural damage for continuous health monitoring. A Kinetic Energy optimization technique and an Effective Independence Method are analyzed and numerical and theoretical issues are addressed for a cable-stayed bridge. Its application to a cable-stayed bridge is discussed to optimize the sensor placement for identification and control purposes.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3745-3765
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• 2022

The concrete structures related to nuclear safety are threatened by accidental impact loadings, mainly including the low-velocity drop-weight impact (e.g., spent fuel cask and assembly, etc. with the velocity less than 20 m/s) and high-speed projectile impact (e.g., steel pipe, valve, turbine bucket, etc. with the velocity higher than 20 m/s), while the existing studies are still limited in the impact resistant design of nuclear power plant (NPP), especially the primary RC slab. This paper aims to propose the numerical simulation and theoretical approaches to assist the impact-resistant design of RC slab in NPP. Firstly, the continuous surface cap (CSC) model parameters for concrete with the compressive strength of 20-70 MPa are fully calibrated and verified, and the refined numerical simulation approach is proposed. Secondly, the two-degree freedom (TDOF) model with considering the mutual effect of flexural and shear resistance of RC slab are developed. Furthermore, based on the low-velocity drop hammer tests and high-speed soft/hard projectile impact tests on RC slabs, the adopted numerical simulation and TDOF model approaches are fully validated by the flexural and punching shear damage, deflection, and impact force time-histories of RC slabs. Finally, as for the two low-velocity impact scenarios, the design procedure of RC slab based on TDOF model is validated and recommended. Meanwhile, as for the four actual high-speed impact scenarios, the impact-resistant design specification in Chinese code NB/T 20012-2019 is evaluated, the over conservation of which is found, and the proposed numerical approach is recommended. The present work could beneficially guide the impact-resistant design and safety assessment of NPPs against the accidental impact loadings.

• Smart Structures and Systems
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• v.15 no.3
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• pp.593-608
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• 2015

In many of the industrialized countries an increasing amount of infrastructure is ageing. This has become specifically critical to bridges which are a major asset with respect to keeping an economy alive. Life of this infrastructure is scattering but often little quantifiable information is known with respect to its damage condition. This article describes how a damage tolerance approach used in aviation today may even be applied to civil infrastructure in the sense that operational life can be applied in the context of modern life cycle management. This can be applied for steel structures as a complete process where much of the damage accumulation behavior is known and may even be adopted to concrete structures in principle, where much of the missing knowledge in damage accumulation has to be substituted by enhanced inspection. This enhanced and continuous inspection can be achieved through robotic systems in a first approach as well as built in sensors in the sense of structural health monitoring (SHM).

• Journal of the Korea Safety Management & Science
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• v.13 no.2
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• pp.1-8
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• 2011

The Chicago Convention in 1944 made important contributions to aviation safety improvement, building an aviation safety monitoring system for its signatory countries. As ICAO is now on the verge of changing its supervision system from self-reporting to preventive Continuous Monitoring Approach(CMA) in 2013, we also expect our own safety system to make a progress accordingly. The government is pushing ahead with plans to build an integrated safety management system at government level that satisfies international standards and reflects domestic features. To this end, this report proposes the most effective system-building model, by analyzing the current status of the system that is in use and meets the requirements of international aviation agencies.

• The Korean journal of internal medicine
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• v.39 no.3
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• pp.373-382
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• 2024

This review addresses the escalating challenge posed by antibiotic resistance, highlighting its profound impact on global public health, including increased mortality rates and healthcare expenditures. The review focuses on the need to adopt the One Health approach to effectively manage antibiotic usage across human, animal, and environmental domains. Antimicrobial stewardship programs (ASPs) are considered as comprehensive strategies that encompass both core and supplementary initiatives aimed at enhancing prudent antibiotic use. The 2021 "Guidelines on Implementing ASP in Korea" introduced such strategies, with a strong emphasis on fostering multidisciplinary and collaborative efforts. Furthermore, the "Core Elements for Implementing ASPs in Korean General Hospitals," established in 2022, provide a structured framework for ASPs, delineating leadership responsibilities, the composition of interdisciplinary ASP teams, a range of interventions, and continuous monitoring and reporting mechanisms. In addition, this review examines patient-centric campaigns such as "Speak Up, Get Smart" and emphasizes the pivotal role of a multidisciplinary approach and international cooperation in addressing the multifaceted challenges associated with antibiotic resistance.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.785-793
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• 2022

In this study, tomato maturity was estimated based on deep learning for a harvesting robot. Tomato images were obtained using a RGB camera installed on a monitoring robot, which was developed previously, and the samples were cropped to 128 × 128 size images to generate a dataset for training the classification model. The classification model was constructed based on convolutional neural networks, and the mean-variance loss was used to learn implicitly the distribution of the data features by class. In the test stage, the tomato maturity was estimated as a continuous index, which has a range of 0 to 1, by calculating the expected class value. The results show that the F1-score of the classification was approximately 0.94, and the performance was similar to that of a deep learning-based classification task in the agriculture field. In addition, it was possible to estimate the distribution in each maturity stage. From the results, it was found that our approach can not only classify the discrete maturation stages of the tomatoes but also can estimate the continuous maturity.