• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.123-128
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• 2023

This paper presents the results of an analysis of the discrimination accuracy of a bridge load carrying capacity estimation model based on data from inspection reports. The load carrying rate estimation model was derived using statistical methods through the collection of 2,161 inspection reports. By entering the bridge specifications and maintenance information, you can check the estimated load carrying capacity of the bridge. In order to verify the discrimination accuracy of the estimated load carrying rate model, the estimated load carrying rate was compared with the load carrying rate in the inspection and diagnosis report for 164 public bridges for which data was available. Although there are differences depending on the bridge type, the results were obtained with an accuracy of over 80% in determining the estimated load carrying capacity.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.171-175
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• 2016

본 연구는 SNS 문서의 논쟁 유발성을 자동으로 감지하기 위한 연구이다. 논쟁 유발성 분류는 글의 주제와 문체, 뉘앙스 등 추상화된 자질로서 인지되기 때문에 단순히 n-gram을 보는 기존의 어휘적 자질을 이용한 문서 분류 기법으로 해결하기가 어렵다. 본 연구에서는 문서 전체에서 전역적으로 나타난 추상화된 자질을 학습하기 위해 2-phase CNN 기반 논쟁 유발성 판별모델을 제안한다. SNS에서 수집한 글을 바탕으로 실험을 진행한 결과, 제안하는 모델은 기존의 문서 분류에서 가장 많이 사용된 SVM에 비해 월등한 성능 향상을, 단순한 CNN에 비해 상당한 성능 향상을 보였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.568-570
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• 2022

객체 유사도를 판별하는 기술은 정보 처리의 여러 분야에서 응용되고 있다. 본 연구에서는 현장 자연어 텍스트 데이터셋과 딥러닝 모델을 이용하여 챗봇 등에서 응용되는 데이터 유사성을 판별하고, 해당 모델의 성능을 측정해보았다.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.295-301
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• 2021

Individual mental fatigue not only reduces cognitive ability and work performance, but also becomes a major factor in large and small accidents occurring in daily life. In this paper, a CNN model for EEG-based mental fatigue discrimination was proposed. To this end, EEG in the resting state and task state were collected and applied to the proposed CNN model, and then the model performance was analyzed. All subjects who participated in the experiment were right-handed male students attending university, with and average age of 25.5 years. Spectral analysis was performed on the measured EEG in each state, and the performance of the CNN model was compared and analyzed using the raw EEG, absolute power, and relative power as input data of the CNN model. As a result, the relative power of the occipital lobe position in the alpha band showed the best performance. The model accuracy is 85.6% for training data, 78.5% for validation, and 95.7% for test data. The proposed model can be applied to the development of an automated system for mental fatigue detection.

• Proceedings of the KIEE Conference
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• 2007.11b
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• pp.279-281
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• 2007

본 논문에서는 계층적 SVM을 이용한 전력용 변압기의 고장진단 기법을 제안한다. 제안된 기법은 전처리 과정, 정상/고장판별 부, 고장원인판별부, 열화추이분석부로 구성된다. 제안한 고장진단과정을 보면, 전처리부에서는 DGA에 의해 얻어진 가스 데이터의 특징벡터를 산출한다. 그 다음단계로 정상/고장 판별부에서는 얻어진 특징벡터를 이용하여 SVM에 의해 정상/고장 여부를 진단한다. 고장원인 판별부에서는 진단하고자 하는 변압기가 고장으로 판정이 난 경우에 다중-클래스 SVM에 의해 고장원인을 판정한다. 또한 정상/고장판별에서 정상이라 판정할 지라도 열화추이분석부에서 FCM에 의해 구축된 고장모델과 정상데이터간의 거리척도를 이용하여 고장추이론 분서한다. 제안된 방법의 유용성을 보이기 위한 실험결과에서 기존의 방법들에 비해서 향상된 진단결과를 보임을 확인하였다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.2012-2013
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• 2007

현재 개발된 분산전원 단독운전 판별기법중 하나인 무효전력주입방식은 판별성능은 우수하나 정격의 $2.5{\sim}5%$의 무효전력을 주입하므로 계통전압에 고조파를 발생하여 전력품질을 저하하는 단점을 갖는다. 본 논문에서는 적은 양의 연속적인 무효전력을 주입하므로 전력품질 저하를 최소화하고 동시에 검출성능이 우수한 인버터연계방식 분산전원의 단독운전 판별기법을 개발하였다. 개발한 판별기법의 타당성을 검증하기위해 EMTDC 소프트웨어를 이용하여 전체시스템의 시뮬레이션모델을 개발하여 시뮬레이션을 실시하였다.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.12
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• pp.889-898
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• 2013

Due to the popularization of high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy to make high-quality counterfeit money. However, the probability of detecting counterfeit money to the general public is extremely low and the detection device is expensive. In this paper, a counterfeit money detection algorithm using a general purpose scanner and computer system is proposed. First, the printing features of color printers are calculated using morphological operations and gray-level co-occurrence matrix. Then, these features are used to train a support vector machine classifier. This trained classifier is applied for identifying either original or counterfeit money. In the experiment, we measured the detection rate between the original and counterfeit money. Also, the printing source was identified. The proposed algorithm was compared with the algorithm using wiener filter to identify color printing source. The accuracy for identifying counterfeit money was 91.92%. The accuracy for identifying the printing source was over 94.5%. The results support that the proposed algorithm performs better than previous researches.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.101-112
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• 1999

Traffic accidents increase with the increase of the vehicles in operation on the street. Especially big traffic accidents composed of over 3 killed or 20 injured accidents with the property damage become one of the serious problems to be solved in most of the cities. The purpose of this study is to build the discrimination model on big traffic accidents using the Quantification II theory for establishing the countermeasures to reduce the big traffic accidents. The results are summarized as follows. 1)The existing traffic accident related model could not explain the phenomena of the current traffic accident appropriately. 2) Based on the big traffic accident types vehicle-vehicle, vehicle-alone, vehicle-pedestrian and vehicle-train accident rates 73%, 20.5% 5.6% and two cases respectively. Based on the law violation types safety driving non-fulfillment center line invasion excess speed and signal disobedience were 48.8%, 38.1% 2.8% and 2.8% respectively. 3) Based on the law violation types major factors in big traffic accidents were road and environment, human, and vehicle in order. Those factors were vehicle, road and environment, and human in order based on types of injured driver’s death. 4) Based on the law violation types total hitting and correlation rates of the model were 53.57% and 0.97853. Based on the types of injured driver’s death total hitting and correlation rates of the model were also 71.4% and 0.59583.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.81-87
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• 2009

Recently RFID system has been adopted in various fields rapidly. However, we ought to solve the problem of privacy invasion that can be occurred by obtaining information of RFID Tag without any permission for popularization of RFID system To solve the problems, it is Ohkubo et al.'s Hash-Chain Scheme which is the safest method. However, this method has a problem that requesting lots of computing process because of increasing numbers of Tag. Therefore, in this paper we apply the previous method into the grid environment by analyzing Hash-Chain scheme in order to reduce processing time when Tags are identified. We'll implement the process by offering Tag Identification Process Model to divide SPs evenly by node.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.513-514
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• 2023

초해상은 저해상도의 영상을 고해상도 영상으로 합성하는 기술이다. 이 기술에 딥러닝이 적용되어, 2014년에는 SRCNN(Super Resolution Convolutional Neural Network) 모델이 발표됐다. 이후에는 SRCAE(Super Resolution Convolutional Autoencoders)와 GAN(Generative Adversarial Networks)을 기반으로 한 SRGAN(Super Resolution Generative Adversarial Networks) 등, SRCNN의 성능을 능가하는 모델들이 발표됐다. ESRGAN(Enhanced Super Resolution Generative Adversarial Networks)은 SRGAN 모델의 성능을 개선했지만, 완벽한 성능을 내지 못하는 문제점이 있다. 이에 본 논문에서는 판별자(Discriminator) 구조를 변경하여 ESRGAN의 성능을 개선한다. 실험 결과, 제안하는 모델이 ESRGAN보다 더 높은 성능을 보일 것으로 기대된다.