• Journal of KIISE
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• v.43 no.6
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• pp.718-723
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• 2016

In streaming data analysis, detecting concept drift accurately is important to maintain the performance of classification model. Error rates are usually used for concept drift detection. However, by describing prediction results with only binary values of 0 or 1, useful information about a behavior pattern of a classifier can be lost. In this paper, we propose an effective concept drift detection method which describes performance pattern of a classifier by utilizing probability estimates for class prediction and detects a significant change in a classifier behavior. Experimental results on synthetic and real streaming data show the efficiency of the proposed method for detecting the occurrence of concept drift.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.493-498
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• 2005

In this paper, we deal with on observer design for detecting the human faults in container crane operation. First we propose an observer for detecting the human faults and show the existing condition for the observer. In this case, we assume that the human faults can be considered ad a careless mistake during the crane operation. In simulation, we used the previous results for human work model and design the observer for the human work model. As a simulation results with human faults, the proposed observer can detected the human faults perfectly, thus the efficiency of proposed observer is shown.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.28-34
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• 2002

Irregular reflected signals on a sea surface make clutters to a ship's radar image. Clutters are similar to Gaussian white noises which are very harmful for detecting objecting at sea by a ship's radar. To remove the clutter effects, many papers show the algorithms by antenna, filters, and so on. This paper shows a new algorithm which uwes Wavelet and Morphology median filter conceps for removing clutter and enhancing image in order to detect well a distressed of being rescued ship in a rough weather condition at sea.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.360-365
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• 2010

In this paper, we present a distributed algorithm for detecting dynamic event regions in wireless sensor network with the consideration on energy saving. Our model is that the sensing field is monitored by a large number of randomly distributed sensors with low-power battery and limited functionality, and that the event region is dynamic with motion or changing the shape. At any time that the event happens, we need some sensors awake to detect it and to wake up its k-hop neighbors to detect further events. Scheduling for the network to save the total power-cost or to maximize the monitoring time has been studied extensively. Our scheme is that some predetermined sensors, called critical sensors are awake all the time and when the event is detected by a critical sensor the sensor broadcasts to the neighbors to check their sensing area. Then the neighbors check their area and decide whether they wake up or remain in sleeping mode with certain criteria. Our algorithm uses only 2 bit of information in communication between sensors, thus the total communication cost is low, and the speed of detecting all event region is high. We adapt two kinds of measure for the wake-up decision. With suitable threshold values, our algorithm can be applied for many applications and for the trade-off between energy saving and the efficiency of event detection.

• Analytical Science and Technology
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• v.11 no.3
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• pp.167-173
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• 1998

An electrothermal vaporization-hollow cathode glow discharge-atomic emission spectrometer(ETV-HCGD-AES) has been developed for detecting heavy metals in human serum and urine samples. Fisrt of all, we designed a glow discharge cell for atomic emission spectrometry and its analytical performance was studied with the standard reference materials(SRMs) purchased from the NIST. Practically, the ETV-HCGD-AES demonstrated better instrumental sensitivity and selectivity for detecting Hg and Pb in the SRMs, serum and urine, than ICP-OES since the ETV-HCGD-AES was not required the complicate sample digestion procedure, which improved sample transportation efficiency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.6
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• pp.1454-1460
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• 1998

In this ppaer, we propose a new detector based on the median-shift sign, and then investigate its asymptotic and finite sample-size performance. We call it the median-shift sign (MSS) detector, which is an extension of the classical sign detector. First, we consider the asymptotic opti$$\mu$ median shift values and their characteristics. Next, we consider the asymptotic relative efficiency of the MSS detectors. we then consider the problem of detecting known signals in noise of known probability density function, and the problem of detecting known signals when only partial information is available on the noise.

• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• Journal of Microbiology
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• v.35 no.3
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• pp.177-180
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• 1997

The purpose of this study was to evaluate the efficiency of Line Probe Assay (LiPA) in detecting the rpoB gene mutation of clinically isolated Mycobacterium tuberculosis (MTB) and to compare the level of resistance to the various rifamycins with their mutation sites. The mutation in the rpoB gene was found in 84 (97.6%) out of 86 rifampicin (RMP) resistant strains as determined by LiPA. No mutation was observed in 2 RMP resistant strains and in any of 38 RMP susceptible strains tested. Only one of 3 strains with .DELTA.5/R5, one of 2 strains with .DELTA.3, and one of 3 strains with .DELTA.2/R2 LiPA profile showed a slightly lower level of resistance to the rifapentine than the other strains. Although we could not find correlations between mutation sites in the rpoB gene and the level of susceptibility to the various rifamycins, the LiPA is recommended as a fast screening tool for detection of RMP resistant MTB.

• Advances in aircraft and spacecraft science
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• v.9 no.4
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• pp.279-300
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• 2022

This paper analyzes the possibilities of a new method to using TLE data for detecting satellite maneuvers. The method has a number of advantages over other methods that are designed to detect maneuvers. It allows not only to detect maneuvers, but also to get a more complete picture of the maneuver. In particular, the method makes it possible to estimate the moments of the beginning and end of the maneuver, calculate the changes in the orbital elements, evaluate the tangential and binormal components of the impulse, and finally, calculate the impulse of the satellite obtained as a result of the maneuver. To demonstrate in detail the capabilities of the algorithm, the proposed method was applied to one of LEO satellites - TIANHUI-1 satellite. After the efficiency of the method was proved, this method was applied to the China Space Station - TIANHE-1 (CSS), Starlink-1095 and Starlink-2305 satellites. The maneuvers of the CSS and Starlink-1095 satellite during their close encounter on 1 July, 2021, and the CSS and Starlink-2305 satellite during their close encounter on 21 October, 2021 are analyzed in detail. The minimum distances between the CSS and Starlink satellites at the moments of their maximum approaches are estimated. An estimate of the computation time of this algorithm is given, and the possibility of its use for monitoring maneuvers or other anomalous orbital changes of a large number of satellites in near real-time is shown. It is assumed that on the basis of this method, a service for monitoring satellite maneuvers can be created.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.72.1-72.1
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• 2013

Even though current microlensing follow-up observations focus on high-magnification events due to the high efficiency of planet detection, it is very difficult to do a confident detection of planets in high-magnification events with extremely weak central perturbations (i.e., the fractional deviation is ${\delta}{\leq}0.02$). For the confident detection of planets in the extremely weak central perturbation events, it is needed both the high cadence monitoring and the high photometric accuracy. A next-generation ground-based observation project, KMTNet (Korea Microlensing Telescope Network), satisfies both the conditions. Here we investigate how well planets in high-magnification events with extremely weak central perturbations are detected by KMTNet. First, we determine the probability of occurrence of events with ${\delta}{\leq}0.02$. From this, we find that for ${\leq}100M_E$ planets in the separation of $0.2AU{\leq}d{\leq}20AU$, events with ${\delta}{\leq}0.02$ occur with a frequency of more than 70%, in which d is the projected planet-star separation. Second, we estimate the efficiency of detecting planetary signals in the events with ${\delta}{\leq}0.02$ via KMTNet. We find that for main-sequence and subgiant source stars, ${\geq}1M_E$ planets can be detected more than 50% in a certain range that has the efficiency of ${\geq}10%$ and changes with the planet mass.