• Proceedings of the KSR Conference
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• 1998.05a
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• pp.604-611
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• 1998

High-speed railway trains entering and leaving tunnels generate finite amplitude pressure wave which propagate back and forth along the tunnels, reflecting at the open ends of the tunnels and at other discontinuities such as ventilation shafts and the train themselves. In present day railways, the magnitudes of the pressure waves are much too small to cause structual damage, but they are a serious potential source of aural discomport for passengers on unsealed trains. Almost always do the pressure waves propagating along the tunnels lead to a hazardous impulse noise near the exit portal of the tunnel. In order to alleviate such undesirable phenomena, some control strategies have been applied to the compression wave propagating inside the tunnel. The objective of the current work is to investigate the effect of tunnel entrance hoods on the entry compression wave at the vicinity of the tunnel entrance. Three types of entrance hoods were tested by the numerical method using the characteristics of method for a wide range of train speeds. The results show that the maximum pressure gradient of compression wave can be considerably reduced by the tunnel entrance hood. Desirable hood shape for reduction of the pressure transients and impulse noise was found to be of abrupt type hood with its cross-sectional area 2.5times the tunnel area.

• Smart Structures and Systems
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• v.12 no.5
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• pp.547-577
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• 2013

To suppress vibration and noise of mechanical structures piezoelectric ceramics play an increasing role as effective, simple and light-weighted damping devices as they are suitable for sensing and actuating. Out of the various piezoelectric damping methods this paper compares mode based active control strategies to passive shunt damping for thin plates. Therefore, a new approach for the optimal placement of the piezoelectric sensors/actuators, or more general transducers, is proposed after intense theoretical investigations based on the Kirchhoff kinematical hypotheses of plates; in particular, modal and nilpotent transducers are discussed in detail. Based on the proposed distribution a discrete design for modal transducers is implemented, tested and verified on an experimental setup. For active control the modal sensors clearly identify the eigenmodes, whereas the modal actuators impose distributed eigenstrains in order to reduce the transverse plate vibrations. In contrast to the modal control, passive shunt damping works without requiring additional actuators or auxiliary power and can therefore act as an autonomous system, but it is less effective compensating the flexible vibrations. Exemplarily, an acryl glass plate disturbed by an arbitrary force initialized by a loudspeaker is investigated. Comparing the different methods their specific advantages are highlighted and a significant broadband reduction of the vibrations of up to -20dB is obtained.

• Journal of Microbiology and Biotechnology
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• v.29 no.10
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• pp.1522-1542
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• 2019

To adapt to environmental changes and to maintain cellular homeostasis, microorganisms adjust the intracellular concentrations of biochemical compounds, including metal ions; these are essential for the catalytic function of many enzymes in cells, but excessive amounts of essential metals and heavy metals cause cellular damage. Metal-responsive transcriptional regulators play pivotal roles in metal uptake, pumping out, sequestration, and oxidation or reduction to a less toxic status via regulating the expression of the detoxification-related genes. The sensory and regulatory functions of the metalloregulators have made them as attractive biological parts for synthetic biology, and the exceptional sensitivity and selectivity of metalloregulators toward metal ions have been used in heavy metal biosensors to cope with prevalent heavy metal contamination. Due to their importance, substantial efforts have been made to characterize heavy metal-responsive transcriptional regulators and to develop heavy metal-sensing biosensors. In this review, we summarize the biochemical data for the two major metalloregulator families, SmtB/ArsR and MerR, to describe their metal-binding sites, specific chelating chemistry, and conformational changes. Based on our understanding of the regulatory mechanisms, previously developed metal biosensors are examined to point out their limitations, such as high background noise and a lack of well-characterized biological parts. We discuss several strategies to improve the functionality of the metal biosensors, such as reducing the background noise and amplifying the output signal. From the perspective of making heavy metal biosensors, we suggest that the characterization of novel metalloregulators and the fabrication of exquisitely designed genetic circuits will be required.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.6
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• pp.41-48
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• 2002

This study is on the structural control experiment for a small scale three-story building structure employing on active mass damper subjected to earthquake loading. $\mu$-synthesis controllers, which belong to robust control strategies, were designed and their performance were experimentally verified. Frequency-dependent weighting functions corresponding to disturbance input and controlled output were defined and combined to produce optimal $\mu$-synthesis controllers. The experiment result shows 60-70% reduction in RMS responses under the band-limited white noise excitation and 30-45% reduction in peak responses under the scaled earthquake excitations. Good agreement was obtained between the simulations based on the identified mathematical model and experimental results. And the simulations for the system with uncertainties show that the designed controllers are robust within a specified range of uncertainties.

• Journal of Environmental Impact Assessment
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• v.20 no.3
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• pp.397-409
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• 2011

This study was carried out for improving the effectiveness of water resources development project through local resident opinions in the environmental impact assessment(EIA). The EIA reports of seven dams were examined. Four dams -Youngju Dam, Seongduck Dam, Buhang Dam and Hantangang Dam- which included many local opinions including 470 opinions of 341 local residents were selected to be analyzed. Local residents submitted their opinions in the six fields which are meteorological phenomena, water quality, land use, fauna and flora, noise and vibration, and residence, and the major opinions of those opinions came from the atmosphere environment field which is 32% of total opinions and social and economic field which is 38% of total opinions, respectively. In submerged area, opinions of the measure for migration and compensation were 91% and in non-submerged area, opinions of the measure for meteorological phenomena was 86%. Those percentages were maximum in each area. Opinions concerned meteorological phenomena were 86% and 53% in Youngju Dam and Seongduck Dam where area is surrounded by existing dam, but there was only 9% and 0% of opinions in Buhang Dam and Hantangang Dam where area is without existing dam nearby. The reformation methods which reflected the resident's opinions were suggested on EIA in dam development projects. First of all, reliability and objectivity of the field of meteorological phenoma should be enhanced by scientific prediction of the phenomenon days. Secondly, techniques reducing uncertainty of various water quality prediction models ought to be developed and effectiveness of the reduction strategies in environmental impact should be quantified. Finally, the draft of EIA report should involve the detailed plans of migration and compensation's procedures, criteria and measures to support.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1401-1411
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• 2023

In the face of escalating utilization of the marine spatial domain, conflicts have emerged among stakeholders, necessitating effective management strategies beyond conventional government permits and regulations. Particularly within the domain of aquaculture, operational oversight relies on a localized licensing system, posing challenges in accurately assessing the prevailing circumstances. This research employs synthetic aperture radar (SAR) imagery as a tool to monitor coastal aquaculture fish farms, aimed at enhancing insights into management protocols. Leveraging Sentinel-1A imagery and time series SAR data integration, a superimposition technique is utilized, facilitating noise reduction while retaining crucial information regarding smaller-scale facilities, such as fish farms. Through analysis of VH polarization data, a detection overall accuracy of approximately 88% for coastal fish farms was achieved. The findings of this study offer potential applications in the continuous monitoring of aquaculture farms in correspondence with seasonal variations in aquaculture yields, thereby proposing frameworks for the establishment of effective management cycles for marine space utilization.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1054-1065
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• 1993

A computer simulation is performed on the effectiveness of the active minimization of harmonically excited enclosed sound fields for producing global reduction in the amplitude of the pressure fluctuations. In this study for the appreciable reductions in total time averaged acoustic potential energy, $E_{pp}$, the transducer location strategies for three dimensional active noise control is presented based on a state space modal which approximates the closed acoustic field.In this study, the above theoretical basis is used to investigate the application of active control to sound fields of low modal density. By the used of room-like 3-dimensional rectangular enclosure it is demonstrated that the reductions in $E_{pp}$ can be achieved by using a single secondary source, provided that the source is placed within the half a wavelength from the primary source and placed away from nodal line of the sound field. Concerning the reductions in $E_{pp}$ by minimzing the pressure in sound fields by the use of 3-dimensional rectangular enclosure, the effects of the number of sensors and the locations of these sensors are investigated. When a few modes dominate the response it is found that if only a limited number of sensors are located away from nodal line and located at the pressure maxima of the sound field such as at each corner of a rectangular enclosure.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.