• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.71-82
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• 2022

In order to replace the sampling tensile test of products produced in the tab welding process, which is one of the automotive battery manufacturing processes, vision inspectors are currently being developed and used. However, the vision inspection has the problem of inspection position error and the cost of improving it. In order to solve these problems, there are recent cases of applying deep learning technology. As one such case, this paper tries to examine the usefulness of applying Faster R-CNN, one of the deep learning technologies, to existing product inspection. The images acquired through the existing vision inspection machine are used as training data and trained using the Faster R-CNN ResNet101 V1 1024x1024 model. The results of the conventional vision test and Faster R-CNN test are compared and analyzed based on the test standards of 0% non-detection and 10% over-detection. The non-detection rate is 34.5% in the conventional vision test and 0% in the Faster R-CNN test. The over-detection rate is 100% in the conventional vision test and 6.9% in Faster R-CNN. From these results, it is confirmed that deep learning technology is very useful for detecting welding error of lead tabs in automobile batteries.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.649-664
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• 2011

Cooperative spectrum sensing (CSS) with decision fusion is considered as a key technology for tackling the challenges caused by fading/shadowing effects and noise uncertainty in spectrum sensing in cognitive radio. However, most existing solutions assume an error-free decision transmission, which is obviously not the case in realistic scenarios. This paper extends the general decision-fusion-based CSS scheme by considering the fading/shadowing effects and noise corruption in the common control channels. With this more practical model, the fusion centre first estimates the local decisions using a binary minimum error probability detector, and then combines them to get the final result. Theoretical analysis and simulation of this CSS scheme are performed over typical channels, which suggest some performance deterioration compared with the pure case that assumes an error-free decision transmission. Furthermore, the fusion strategy optimization in the proposed cooperation model is also investigated using the Bayesian criteria. The numerical results show that the total error rate of noisy CSS is higher than that of the pure case, and the optimal values of fusion parameter in the counting rule under both cases decrease as the local detection threshold increases.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.17 no.2
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• pp.62-67
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• 2009

LOSA is a flight safety program that analyses human errors in normal operations. Trained pilot observers monitor the normal flights at the observer seat. LOSA is a proactive non jeopardy data collection tool using threat and error management(TEM) as a framework. With the analysis of crew behaviors through LOSA with The LOSA collaborative(TLC), the airlines can identify the behaviors of the crew during normal operations. The major objective of LOSA is to measure how the crew manage threats, errors and undesired aircraft deviations in the cockpit on day to day operations. The airlines are able to set up effective TEM training with practical six generation Crew recourse management(CRM) with data of error from LOSA instead of theoretical CRM courses. The Airlines can use TEM as an integral part of a Safety Management System(SMS) and uses monitoring and cross-checking skills in the flight operations to manage threats and errors effectively when we know the errors we make in the cockpit on daily operation. The result of LOSA indicates that the error detection rate should be enhanced since around the half of the errors went undetected. The areas which should be focused for enhancing the error detection are monitor, cross-check, the management of workload, automation and taxiway/ runway to manage errors effectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.721-728
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• 2018

This paper introduces various linear block error correction code and compares performances of the correction circuits. As the risk of errors due to power noise has increased, ECC(: Error Correction Code) has been introduced to prevent the bit error. There are two representatives of ECC structures which are SEC-DED(: Single Error Correction Double Error Detection) and SEC-DED-DAEC(: Double Adjacent Error Correction). According to simulation results, the SEC-DED circuit has advantages of small area and short delay time compared to SEC-DED-DAEC circuits. In case of SED-DED-DAEC, there is no big difference between Dutta's and Pedro's from performance point of view. Therefore, Pedro's code is more efficient than Dutta' code since the correction rate of Pedro's code is higher than that of Dutta's code.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.3
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• pp.45-50
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• 2007

We present a auto compensating quantum key distribution system based on optical fiber at 1550nm. In the quantum key transmission system, main control board and phase modulation driving board are fabricated for auto controlling quantum key distribution(QKD). We tested the single photon counts per dark counts for a single photon detector, quantum key distribution rate($R_{sift}$) and the quantum bit error rate (QBER). Quantum bit error rate of 3.5% in 25km QKD is obtained. This system is commercially available.

• ETRI Journal
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• v.24 no.2
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• pp.161-171
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• 2002

This paper proposes a novel decision feedback differential phase detection (DF-DPD) for M-ary DPSK. A conventional differential phase detection method for M-ary Differential Phase Shift Keying (DPSK) can simplify the receiver architecture. However, it possesses a poorer bit error rate (BER) performance than coherent detection because of the prior noisy phase sample. Multiple-symbol differential detection methods, such as maximum likelihood differential phase detection, Viterbi-DPD, and DF-DPD using L-1 previous detected symbols, have attempted to improve BER performance. As the detection length, L, increases, the BER performance of the DF-DPD improves but the complexity of the architecture increases dramatically. This paper proposes a simplified DF-DPD architecture replacing the conventional delay and additional architecture with an accumulator. The proposed architecture also improves BER performance by minimizing the current differential phase noise through the accumulation of previous differential phase noise samples. The simulation results show that the BER performance of the proposed architecture approaches that of a coherent detection with differential decoding.

• Journal of Astronomy and Space Sciences
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• v.27 no.3
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• pp.221-230
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• 2010

A 4+12+16 amplitude phase shift keying (APSK) modulation outperforms other 32-APSK modulations in a nonlinear additive white Gaussian noise (AWGN) channel because of its intrinsic robustness against AM/AM and AM/PM distortions caused by the nonlinear characteristics of a high-power amplifier. Thus, this modulation scheme has been adopted in the digital video broadcasting-satellite2 European standard. And it has been considered for high rate transmission of telemetry data on deep space communications in consultative committee for space data systems which provides a forum for discussion of common problems in the development and operation of space data systems. In this paper, we present an improved bits-to-symbol mapping scheme with a better bit error rate for a 4+12+16 APSK signal in a nonlinear AWGN channel and propose a simple signal detection algorithm for the 4+12+16 APSK from the presented bit mapping.

• The Journal of the Acoustical Society of Korea
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• v.13 no.5
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• pp.77-82
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• 1994

In speech signal processing, it is very important to detect the pitch exactly. Although various methods for detecting the pitch of speech signals have been developed, it is difficult to exactly extract the pitch for wide range of speakers and various utterances. Thus we propose a new pitch detection algorithm which takes advantage of the G-peak extraction. It is a method to detect the pitch period of the voiced signals by finding MZCI (maximum zero-crossing interval) of the G-peak which is defined as cut-off bandwidth rate of LPF (low pass filter). This algorithm performs robustly with a gross error rate of 3.63% even in 0 dB SNR environement. The gross error rate for clean speech is only 0.18%. Also it is able to process all courses with high speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.15-20
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• 2016

Compared to the MIMO system using the spatial multiplexing methods and the MIMO system using the diversity scheme achieved a high rate, but the lower the diversity gain to improve the data transmission reliability should separate the spatial stream at the MIMO receiver. In this paper, we compared Channel capacity detection methods with the Lattice code, the 3-user interference channel and linear channel interference detection methods ZF (Zero Forcing) and MMSE (Minimum Mean Square Error) detection methods. The channel is a Diagonal channel. In other words, Diagonal channel is confirmed by the inverse matrix satisfies the properties of Jacket are element-wise inverse to $[H]_N[H]_N^{-1}=[I]_N$.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.576-586
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• 2020

Analyzing baseball games using sensors such as radars or riders is expensive. In this paper, we propose an algorithm to detect pitch shots and hit shots using baseball video and to generate ball trajectories within hit shots using camera movement. After the pitch shot and the hit shot detection using object detection and optical flow, we generate the transformation relationship between frames and ball locations in the frame, and calculates the ball trajectory. The performance of the proposed method is evaluated for three KBO baseball video sequences, and the detection accuracy and detection rate of pitch shot and hit shot were within 89-95 [%], and the average error for shot range was 13.6[m], The direction error was 7.5° and foul classification accuracy was 98.6%.