• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.154-160
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• 2017

In this paper, we studied the Bartlett method to correctly estimate the targets of a unmanned vehicles. The Bartlett method estimates the desired signals by making the gain constant for the received signal incident on the array antenna. In this paper, the weights of the Bartlett method are updated by applying the winner method and steepest descent method in order to estimation the accurate unmanned. The updated weights improve the resolution of the existing Bartlett method by applying optimal weights to all received signals received at the array antenna. Through simulation, we are comparative analysis about the performance of proposed method. From result of simulation, We showed the superior performance of the proposed method relative to the classical method, and Bartlett using steep descent method showed more superior than one using wiener method.

• The KIPS Transactions:PartD
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• v.14D no.7
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• pp.829-840
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• 2007

Dirty Data Cleansing technique so far have aimed to integrate large amount of data from various sources and manage data quality resided in DB so that it enables to extract meaningful information. Prompt response to varying environment is required in order to persistently survive in rapidly changing business environment and the age of limitless competition. As system requirement is recently getting complexed, Service Oriented Architecture is proliferated for the purpose of integration and implementation of massive distributed system. Therefore, SOA necessarily needs Data Exchange among services through Data Cleansing Technique. In this paper, we executed quality management of XML data which is transmitted through events between services while they are integrated as a sole system. As a result, we developed Dirty Data Cleansing Service based on SOA as focusing on data cleansing between interactive services rather than cleansing based on detection of data error in DB already integrated.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.569-576
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• 2000

The GST can extract the position of facial features without a prior information in an image. However, this method requires a plenty of the processing time because the mask size to process GST must be larger than the size of object such as eye, mouth and nose in an image. In addition, it has the complexity for the computation of middle line to decide facial features. In this paper, we proposed two methods to overcome these disadvantage of the conventional method. First, we used the reduced image having enough information instead of an original image to decrease the processing time. Second, we used the extracted peak positions instead of the complex statistical processing to get the middle lines. To analyze the performance of the proposed method, we tested 200 images including, the front, rotated, spectacled, and mustached facial images. In result, the proposed method shows 85% in the performance of feature extraction and can reduce the processing time over 53 times, compared with existing method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.516-520
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• 2010

As the substantial increase in battlefield density, multiple and complex weapon system, Ensuring the Survivability of the platform has been emphasized. Most of platforms have equipped with ASE (Aircraft Survivability Equipment) system in order to take action against at modernized hostile weapon under current battlefield. ASE system enhance the survivability of the platform through providing accurate situation awareness information by detecting and countermeasuring hostile threats. One of Key factor of the AE system performance is handling multiple and complex threats. Multiple and complex threat emulation is an effective means of ASE system verification In this study, It discuss system verification method before installation by dealing with complex threat situation consists of individual threat.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.1-8
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• 2008

Generally, moving objects in surveillance video are extracted by background subtraction or frame difference method. However, moving cast shadows on object distort extracted figures which cause serious detection problems. Especially, analyzing vehicle information in video frames from a fixed surveillance camera on road, we obtain inaccurate results by shadow which vehicle causes. So, Shadow Elimination is essential to extract right objects from frames in surveillance video. And we use shadow removal algorithm for vehicle classification. In our paper, as we suppress moving cast shadow in object, we efficiently discriminate vehicle types. After we fit new object of shadow-removed object as three dimension object, we use extracted attributes for supervised learning to classify vehicle types. In experiment, we use 3 learning methods {IBL, C4.5, NN(Neural Network)} so that we evaluate the result of vehicle classification by shadow elimination.

• International Journal of Highway Engineering
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• v.18 no.2
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• pp.37-42
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• 2016

PURPOSES : The objective of this study is to determine the optimal frequency of ground penetrating radar (GPR) testing for detecting the voids under the pavement. METHODS : In order to determine the optimal frequency of GPR testing for void detection, a full-scale test section was constructed to simulate the actual size of voids under the pavement. Voids of various sizes were created by inserting styrofoam at varying depths under the pavement. Subsequently, 250-, 500-, and 800-MHz ground-coupled GPR testing was conducted in the test section and the resulting GPR signals were recorded. The change in the amplitude of these signals was evaluated by varying the GPR frequency, void size, and void depth. The optimum frequency was determined from the amplitude of the signals. RESULTS: The capacity of GPR to detect voids under the pavement was evaluated by using three different ground-coupled GPR frequencies. In the case of the B-scan GPR data, a parabolic shape occurred in the vicinity of the voids. The maximum GPR amplitude in the A-scan data was used to quantitatively determine the void-detection capacity. CONCLUSIONS: The 250-MHz GPR testing enabled the detection of 10 out of 12 simulated voids, whereas the 500-MHz testing allowed the detection of only five. Furthermore, the amplitude of GPR detection associated with 250-MHz testing is significantly higher than that of 500-MHz testing. This indicates that 250-MHz GPR testing is well-suited for the detection of voids located at depths ranging from 0.5~2.0 m. Testing at frequencies lower than 250 MHz is recommended for void detection at depths greater than 2 m.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.6
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• pp.490-500
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• 2000

A new technique for the source location of acoustic emission (AE) in plates whose thichness are close to or thinner than the wavelength has been studied by introducing wavelet transform de-noising technique. The detected AE signals were pre-processed using wavelet transform to be decomposed into the low-frequency, high-amplitude flexural components and the high-frequency, low-amplitude extensional components. If the wavelet transform de-noising was employed, we could successfully filter out the extensional wave component, one of the critical errors of source location in plates by arrival time difference method. The accuracy of source location appeared to be significantly improved and independent of the setting of gain and threshold, plate thickness, sensor-to-sensor distance, and the relative position of source to sensors. Since the method utilizes the flexural component of relatively high amplitude, it could be applied to very large, thin-walled structures in practice.

• Journal of the Korean Magnetics Society
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• v.21 no.5
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• pp.167-173
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• 2011

Underwater static magnetic field signature for the naval ship has been widely used as the detonating source of the influence mine system because it is possible to make an accurate target detection in the near field although the magnetic field falls off relatively fast with distance in comparison with the underwater radiated noise signal. In this paper, we describe the prediction results about the underwater static magnetic field by the ferromagnetic hull, the internal structures and the main on-board equipment for the target vessel using the commercial FEM software. Also we analyze the degaussing effectiveness for the target vessel through the degaussing coils arrangement.

• Journal of the Korean Institute of Gas
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• v.25 no.5
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• pp.57-62
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• 2021

Gas is an energy source widely used in general households and industrial sites, and is also a process material widely used in petrochemical and semiconductor processes. However, while it is easy to use, it can cause large-scale human damage due to leakage, explosion, and human inhalation. Therefore, a gas facility safety management solution that can be safely used at home and industrial sites is essential. In particular, the need to develop advanced gas safety solutions is emerging as gas facilities are aging. In this paper, a technology was developed to measure the presence and concentration of gas leaks from a distance by irradiating photons, the minimum energy unit that can no longer be divided into gas facilities, and analyzing the number of reflected photons. This overcomes technical limitations such as short detection distance and inability to detect fine leaks, which are the limitations of conventional electric/chemical gas sensors or infrared-based gas leak detectors.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.31-37
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• 2021

In this paper, we propose an outlier detection algorithm called C-SCGP to prevent the degradation of localization performance based on RSS (Received Signal Strength) and AOA (Angle of Arrival) in the presence of outliers in wireless sensor networks. Since the accuracy of target estimation can significantly deteriorate due to various cause of outliers such as malfunction of sensor, jamming, and severe noise, it is important to detect and filter out all outliers. The single cluster graph partitioning (SCGP) algorithm has been widely used to remove such outliers. The proposed continuous-SCGP (C-SCGP) algorithm overcomes the weakness of the SCGP that requires the threshold and computing probability of outliers, which are impratical in many applications. The results of numerical simulations show that the performance of C-SCGP without setting threshold and probability computation is the same performance of SCGP.