• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.6
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• pp.1488-1493
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• 2014

Shipping and logistics safety, security system is strengthening worldwide, the development of shipping and logistics safety security core technology for national security logistics system construction has been carried out. Interest in portable radiation detection device capable detecting gamma rays nuclides is increasing. In this paper, I would like to propose the study of resolution enhancement for accurate analysis of nuclides in the platform of the radiation detector portable with Cortex-A9.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.54 no.12
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• pp.553-557
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• 2005

This paper describes the application results of an ultrasonic detection system for the power transformer. The ultrasonic detection system with 6 sensors was applied to detect partial discharge in a 154kV transformer with a dangerous levels of $C_{2}H_{2},\;C_{2}H_4$ and $CH_{4}$ gases. The ultrasonic detection tests were carried out 2 times, respectively, to confirm the existence and location of the partial discharge in the transformer. As a result of internal inspection, the arc trace between the pressure ring and core due to the partial discharge was found at the estimated position based on the amplitude and arriving time of the ultrasonic signals. Therefore, it was verified that the ultrasonic detection system is effective as a preventive diagnosis method for the power transformer. Also, the reliability of the ultrasonic detection system in detecting partial discharges in the transformer was also confirmed. It is expected, therefore, that the ultrasonic detection system will have beneficial effects on applications and verifications in detecting partial discharges for the power transformer.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.625-627
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• 2022

In the construction and development of modern industrial production technology, the traditional technology management mode is faced with many problems such as low qualification rates and high application costs. In the research, an improved workpiece defect detection method based on deep learning is proposed, which can control the application cost and improve the detection efficiency of irregular defects. Based on the research of the current situation of deep learning applications, this paper uses the improved Faster R-CNN network structure model as the core detection algorithm to automatically locate and classify the defect areas of the workpiece. Firstly, the robustness of the model was improved by appropriately changing the depth and the number of channels of the backbone network, and the hyperparameters of the improved model were adjusted. Then the deformable convolution is added to improve the detection ability of irregular defects. The final experimental results show that this method's average detection accuracy (mAP) is 4.5% higher than that of other methods. The model with anchor size and aspect ratio (65,129,257,519) and (0.2,0.5,1,1) has the highest defect recognition rate, and the detection accuracy reaches 93.88%.

• Journal of Wetlands Research
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• v.10 no.2
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• pp.23-37
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• 2008

The vertical distribution of dioxins and hexachlorobenzene(HCB) in a sediment core was investigated to elucidate historical trends of dioxins and HCB deposited into Upo wetland. The total concentration of dioxin ranged from 8.7 to 66.27 pg/g-dw in Upo sediments deposited, and from 17.64 to 97.03 pg/g-dw in Mokpo. Dioxin fluxes increased from the first-1990s and then reached a maximum in the mid-1990s. The major source of dioxin by comparing the congeners pattern was pentachlorophenol(PCP) used of agrochemicals. The HCB concentration in most of samples was detected below the MDL(Method Detection Limit of 0.5ng/g), except a few samples.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1998.04a
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• pp.582-589
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• 1998

This paper presents the analysis results of ex-core and in-core neutron noise, acceleration signals and pressure fluctuation measured at Ulchin Nuclear Unit 1 & 2 to identify and monitor the reactor internals vibration including fuel motion. A phase separation algorithm developed by authors was applied to the neutron noises to clearly identify the reactor internals vibratory motion. The beam mode frequency of the core support barrel was identified to be 8Hz and the shell mode to be 20Hz. The first frequency of the fuel assembly was also found to be 3Hz, while first two acoustic frequencies of the primary coolant system were 6 and 17.5Hz. By monitoring and analyzing these frequencies periodically, it is possible to diagnose the operating condition of reactor internals and to provide an early detection of faults for the predictive maintenance.

• Journal of the Korean Society for Nondestructive Testing
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• v.10 no.2
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• pp.15-22
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• 1990

Since in-core flux thimble tube wear the due to flow-induced vibration could degrade the integrity of nuclear reactor, the effective detection and interpretation of the wear is important. In order to establish an inspection technique for thimble tubes, an eddy current experiment was performed to determine the optimum test frequency, defect sensitivity and evaluation accuracy. Eddy current probes were designed and fabricated with a theory. Specimens with artificial defects were fabricated using electro discharge machining method. The results from inspection technique developed and on-site inspection showed good applicability.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.219-222
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• 2012

최근 얼굴검출에 관한 연구는 FPGA를 통한 H/W설계부터 DSP, GPU, ARM Core에 효율적인 S/W 설계까지 다양하게 연구되고 있다. 본 연구에서는 Multi-Core에 효과적인 얼굴검출 방법을 제안한다. 피부색을 통한 얼굴 후보를 추출하고 그 외의 배경 이미지는 삭제하여 연산처리를 빠르게 하였다. Viola-Jones가 제안한 얼굴검출 알고리즘을 POSIX Thread를 사용하여 병렬 처리하였고 그 성능을 단일 코어와 멀티코어에서 측정하였다. 단일 코어에서는 성능의 향상이 없었으나 멀티코어에서는 약 1.8배 속도가 향상되었고 검출 성공률은 기존과 동일하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.836-842
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• 2016

When an accident occurs in the nuclear power plant, the faulted information might mislead to the high possibility of aggravating the accident. At the Fukushima accident, the operators misunderstood that there was no core exposure despite in the processing of core damage, because the instrument information of the reactor water level was provided to the operators optimistically other than the actual situation. Thus, this misunderstanding actually caused to much confusions on the rapid countermeasure on the accident, and then resulted in multiplying the accident propagation. It is necessary to be equipped with the function that informs operators the status of instrument integrity in real time. If plant operators verify that the instruments are working properly during accident conditions, they are able to make a decision more safely. In this study, we have performed various tests for the fault detection sensitivity of an data-driven empirical model to review the usability of the model in the accident conditions. The test was performed by using simulation data from the compact nuclear simulator that is numerically simulated to PWR type nuclear power plant. As a result of the test, the proposed model has shown good performance for detecting the specified instrument faults during normal plant conditions. Although the instrument fault detection sensitivity during plant accident conditions is lower than that during normal condition, the data-drive empirical model can be detected an instrument fault during early stage of plant accidents.

• ETRI Journal
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• v.37 no.6
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• pp.1143-1153
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• 2015

In this paper, we propose an efficient architecture for a real-time image stitching engine for vision SoCs found in motor vehicles. To enlarge the obstacle-detection distance and area for safety, we adopt panoramic images from multiple telegraphic cameras. We propose a stitching method based on a fixed homography that is educed from the initial frame of a video sequence and is used to warp all input images without regeneration. Because the fixed homography is generated only once at the initial state, we can calculate it using SW to reduce HW costs. The proposed warping HW engine is based on a linear transform of the pixel positions of warped images and can reduce the computational complexity by 90% or more as compared to a conventional method. A dual-core SW/HW image stitching engine is applied to stitching input frames in parallel to improve the performance by 70% or more as compared to a single-core engine operation. In addition, a dual-core structure is used to detect a failure in state machines using rock-step logic to satisfy the ISO26262 standard. The dual-core SW/HW image stitching engine is fabricated in SoC with 254,968 gate counts using Global Foundry's 65 nm CMOS process. The single-core engine can make panoramic images from three YCbCr 4:2:0 formatted VGA images at 44 frames per second and frequency of 200 MHz without an LCD display.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.978-985
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• 2003

The implementation of abnormal behavior detection IDS is more difficult than the implementation of misuse behavior detection IDS because usage patterns are various. Therefore, most of commercial IDS is misuse behavior detection IDS. However, misuse behavior detection IDS cannot detect system intrusion in case of modified intrusion patterns occurs. In this paper, we apply data mining so as to detect intrusion with only audit data related in intrusion among many audit data. The agent in the distributed IDS can collect log data as well as monitoring target system. False positive should be minimized in order to make detection accuracy high, that is, core of intrusion detection system. So We apply data mining algorithm for prediction of modified intrusion pattern in the level of audit data learning.