• Journal of information and communication convergence engineering
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• v.8 no.2
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• pp.234-237
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• 2010

P300 component of the event-related potential(ERP) has been studied for theoretical, empirical, and clinical applications. Nowadays the 1-, 2-, and 3-stimulus oddball paradigms are used for eliciting P300 component of EEG in the auditory stimulus experiments. In this paper, we used a method to add one more stimulus to the 3-stimulus auditory paradigm. The adding stimulus has not the same volume but the same tone of the target stimulus. The 4-stimulus oddball paradigm to use two targets is used to elicit the P300 event-related potentials. In 4-stimulus oddball paradigm, an infrequent non-target (p=0.10) is presented in addition to two infrequent targets (p=0.10) and a frequent standard (p=0.70). Two target stimuli elicited a P300 component with a parietal maximum distribution. The amplitude of the P300 in target 2 was larger than that in target 1 and the latency of the P300 in target 2 was longer than that in target 1. The P300 component due to target 2 stimuli was larger than that due to target 1 stimuli. The experimental results approve that the 4-stimulus oddball paradigm can elicit P300 component clearly. The results are compared with the results of the traditional oddball paradigm.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.97-110
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• 2012

High performance sensors and modern data logging technology with real-time telemetry facilitate system fault diagnosis in a very precise manner. Fault detection, isolation and identification in fault diagnosis systems are typical steps to analyze the root cause of failures. This systematic failure analysis provides not only useful clues to rectify the abnormal behaviors of a system, but also key information to redesign the current system for retrofit. The main barriers to effective failure analysis are: (i) the gathered data (event) logs are too large in general, and further (ii) they usually contain noise and redundant data that make precise analysis difficult. This paper therefore applies suitable pre-processing techniques to data reduction and feature extraction, and then converts the reduced data log into a new format of event sequence information. Finally the event sequence information is decoded to investigate the correlation between specific event patterns and various system faults. The efficiency of the developed pre-filtering procedure is examined with a terminal box data log of a marine diesel engine.

• Transactions of the Korean Society of Automotive Engineers
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• v.6 no.3
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• pp.115-122
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• 1998

For digital engine control timings, such as ignition, are based on the crank shaft angle. Therefore, it is very important that the angle of the crank shaft can be detected with accuracy for optimal ignition timing. Sequential multi-point injection(MPI) systems that have independent injection events for each cylinder, are used to inject an accurate quantity of fuel, and to cope with varying engine status promptly. In this study the distributorless ignition timing. A crankshaft position sensor has been installed such that it generates a number of pulses per crankshaft revolution to permit accurate detection of the crank shaft angle. An event detecting algorithm has been developed, which detects the crank shaft pulses generated by the position sensor, and the software outputs the required control signals at given crank angle values. We clarified that the hardware method is the best way to increase the performance of the control system, because the event detecting duration T(1+2)max becomes zero.

• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.5
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• pp.29-36
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• 2002

In the maintenance and retrofit planning of a bridge system, the optimal strategy for inspection and repair are suggested by minimizing the expected total life-cycle cost, which includes the initial cost, the costs of inspection, repair, and failure. Degradation of seismic performance is modeled by using a damage function. And failure probability is computed according to the degree of damage detection by random vibration theory and the event tree analysis. As an example to illustrate the proposed approach, a 10-span continuous bridge structure is used. The numerical results show that the optimum number of the inspection and the repair are increased, as the seismic intensity is increased and the soil condition of a site becomes more flexible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.3
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• pp.1123-1140
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• 2019

Many Internet of Things (IoT) applications involving bursty traffic have emerged recently with event detection. A power management scheme qualified for uplink bursty traffic (PM-UBT) is proposed by distinguishing between bursty and general uplink traffic patterns in the IEEE 802.11 standard to balance energy consumption and uplink latency, especially for stations with limited power and constrained buffer size. The proposed PM-UBT allows a station to transmit an uplink bursty frame immediately regardless of the state. Only when the sleep timer expires can the station send uplink general traffic and receive all downlink frames from the access point. The optimization problem (OP) for PM-UBT is power consumption minimization under a constrained buffer size at the station. This OP can be solved effectively by the bisection method, which demonstrates a performance similar to that of exhaustive search but with less computational complexity. Simulation results show that when the frame arrival rate in a station is between 5 and 100 frame/second, PM-UBT can save approximately 5 mW to 30 mW of power compared with an existing power management scheme. Therefore, the proposed power management strategy can be used efficiently for delay-intolerant uplink traffic in event-driven IoT applications, such as health status monitoring and environmental surveillance.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.81-90
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• 2005

In this paper, we propose a novel approach which models multilingual story link detection by adapting the features such as timelines and multilingual spaces as weighting components to give distinctive weights to terms related to events. On timelines term significance is calculated by comparing term distribution of the documents on that day with that on the total document collection reported, and used to represent the document vectors on that day. Since two languages can provide more information than one language, term significance is measured on each language space and used to refer the other language space as a bridge on multilingual spaces. Evaluating the method on Korean and Japanese news articles, our method achieved $14.3{\%}\;and\;16.7{\%}$ improvement for mono- and multi-lingual story pairs, and for multilingual story pairs, respectively. By measuring the space density, the proposed weighting components are verified with a high density of the intra-event stories and a low density of the inter-events stories. This result indicates that the proposed method is helpful for multilingual story link detection.

• Korean Journal of Remote Sensing
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• v.37 no.5_3
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• pp.1389-1403
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• 2021

Disaster management using VHR (very high resolution) satellite images supports rapid damage assessment and also offers detailed information of the damages. However, the acquisition of pre-event VHR satellite images is usually limited due to the long revisit time of VHR satellites. The absence of the pre-event data can reduce the accuracy of damage assessment since it is difficult to distinguish the changed region from the unchanged region with only post-event data. To address this limitation, in this study, we conducted the wildfire-induced change detection on national wildfire cases using post-fire VHR satellite images and GIS (Geographic Information System) data. For GIS data, a national land cover map was selected to simulate the pre-fire NIR (near-infrared) images using the spatial information of the pre-fire land cover. Then, the simulated pre-fire NIR images were used to analyze bi-temporal NDVI (Normalized Difference Vegetation Index) correlation for unsupervised change detection. The whole process of change detection was performed on a superpixel basis considering the advantages of superpixels being able to reduce the complexity of the image processing while preserving the details of the VHR images. The proposed method was validated on the 2019 Gangwon wildfire cases and showed a high overall accuracy over 98% and a high F1-score over 0.97 for both study sites.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.479-487
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• 2021

In this paper, we propose an Sound Event Detection (SED) model using self-training based on a noisy student model. The proposed SED model consists of two stages. In the first stage, a mean-teacher model based on an Residual Convolutional Recurrent Neural Network (RCRNN) is constructed to provide target labels regarding weakly labeled or unlabeled data. In the second stage, a self-training-based noisy student model is constructed by applying different noise types. That is, feature noises, such as time-frequency shift, mixup, SpecAugment, and dropout-based model noise are used here. In addition, a semi-supervised loss function is applied to train the noisy student model, which acts as label noise injection. The performance of the proposed SED model is evaluated on the validation set of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge Task 4. The experiments show that the single model and ensemble model of the proposed SED based on the noisy student model improve F1-score by 4.6 % and 3.4 % compared to the top-ranked model in DCASE 2020 challenge Task 4, respectively.

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.415-422
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• 2021

Cotton is an important fiber crop, and its seeds are used as feed for dairy cattle. Crop biotechnology has been used to improve agronomic traits and quality in the agricultural industry. The frequent unintentional release of LM cotton into the environment in South Korea is attributed to the increased application of living modified (LM) cotton in food, feed, and processing industries. To identify and monitor the LM cotton, a method for detecting the approved LM cotton in South Korea is required. In this study, we developed a method for the simultaneous detection of four LM cotton varieties, MON757, MON88702, COT67B, and GHB811. The genetic information of each LM event was obtained from the European Commission-Joint Research Centre and Animal and Plant Quarantine Agency. We designed event-specific primers to develop a multiplex PCR method for LM cotton and confirmed the specific amplification. Using specificity assay, random reference material(RM) mixture analysis and limit of detection(LOD), we verified the accuracy and specificity of the multiplex PCR method. Our results demonstrate that the method enabled the detection of each event and validation of the specificity using other LM RMs. The efficiency of multiplex PCR was further verified using a random RM mixture. Based on the LOD, the method identified 25 ng of template DNA in a single reaction. In summary, we developed a multiplex PCR method for simultaneous detection of four LM cotton varieties, for possible application in LM volunteer analysis.

• Journal of Applied Biological Chemistry
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• v.52 no.1
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• pp.1-7
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• 2009

For the development of qualitative PCR detection method of genetically modified (CM) rice, rice species-specific gene, OsCc-1 (rice cytochrome c gene), was selected as suitable far use as an endogenous gene in rice. The primer pair OsCytC-5'/3'with 111 bp amplicon was used for PCR amplification of the rice endogenous gene, OsCc-1 and no amplified product was observed from 8 different crops as templates. Qualitative PCR method was carried out with stack traits of L528$\times$CryIAc1 GM rice developed in Korea. For the qualitative PCRs, some primer pairs were designed with a construct-specific and event-specific type based on T-DNA and junction sequences of T-DNA in GM rice. Actck-5'/3' amplifying between actin promoter and OsCK1 gene introduced in LS28 gave rise to an amplicon 306 bp; also, CrLB-5'/3' from CryIAcl and CKRB-5'/3'amplifying the junction region of T-DNA and genome sequence from LS28 as event-specific primers gave rise to an amplicon 142 bp and 91 bp, respectively. These primer pairs for the detection of event-specific targets not produced PCR amplicons on non-CM rice and various crops in contrast to event lines. Therefore, in this study we verified that event-specific primers were effective to specifically detect stack trait lines and demonstrated that this method presented could be provided with the detection-method data for risk assessment analysis of GM rice to be commercialized.