• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.149-154
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• 2008

FCM 기반 RBF 네트워크는 서로 다른 학습 구조가 결합된 혼합형 모델로서, 입력층과 중간층의 학습 구조는 FCM 알고리즘을 적용하고, 중간층과 출력층 사이의 학습 구조는 Max_Min 신경망을 적용한다. 입력층과 중간층의 학습시 입력벡터와 중간층의 노드중에서 중심과 입력벡터간의 가장 가까운 노드를 승자 노드로 선택하여 출력층으로 전달한다. 그리고 중간층과 출력층 사이의 학습 구조는 Max_Min 신경망을 적용하여 중간층의 승자 뉴런이 출력층의 입력벡터로 적용한다. 하지만 많은 패턴이 입력벡터로 제시될 경우 학습 성능이 저하되는 단점이 있다. 따라서 본 논문에서는 중간층과 출력층의 학습 구조인 Max_Min 알고리즘의 학습 성능을 개선시키기 위해 퍼지 제어시스템을 이용하여 학습률을 동적으로 조정하는 퍼지 제어 기법을 이용한 FCM 기반 RBF 네트워크를 제안한다. 제안된 방법의 학습 성능을 평가하기 위하여 컨테이너 영상에서 추출한 숫자, 영문 식별자를 학습 데이터로 적용한 결과, 기존의 ART2 기반 RBF 네트워크보다 학습 시간이 적게 소요되고, 학습의 수렴성이 개선된 것을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.486-492
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• 2003

The vigilance threshold of conventional fuzzy ART algorithm decide whether to permit the mismatch between any input pattern and stored pattern. If the vigilance threshold was large, despite of little difference among input and stored patterns, the input pattern may be classified to new category. On the other hand, if the vigilance threshold was small, the similarity between two patterns may be accepted in spite of lots of difference and the input pattern are classified to category of the stored pattern. Therefore, the vigilance threshold for the image recognition must be experientially set for the good result. Moreover, it may occur in the fuzzy ART algorithm that the information of stored patterns is lost in the weight-adjusting process and the rate of pattern recognition is dropped. In this paper, I proposed the enhanced fuzzy ART algorithm that supports the dynamical setting of the vigilance threshold using the generalized intersection operator of fuzzy logic and the weight value being adaptively set in proportional to the current weight change and the previous weight by reflecting the frequency of the selection of winner node. For the performance evaluation of the proposed method, we applied to the recognition of container identifiers from shipping container images. The experiment showed that the proposed method produced fewer clusters than conventional ART2 and fuzzy ART algorithm. and had tile higher recognition rate.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.369-376
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• 2006

In this paper, we propose an improved fuzzy RBF network which dynamically adjusts the rate of learning by applying the Delta-bar-Delta algorithm in order to improve the learning performance of fuzzy RBF networks. The proposed learning algorithm, which combines the fuzzy C-Means algorithm with the generalized delta learning method, improves its learning performance by dynamically adjusting the rate of learning. The adjustment of the learning rate is achieved by self-generating middle-layered nodes and by applying the Delta-bar-Delta algorithm to the generalized delta learning method for the learning of middle and output layers. To evaluate the learning performance of the proposed RBF network, we used 40 identifiers extracted from a container image as the training data. Our experimental results show that the proposed method consumes less training time and improves the convergence of teaming, compared to the conventional ART2-based RBF network and fuzzy RBF network.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.321-330
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• 2022

Busan New Port manages the largest volume of traffic among Korean ports, and accounts for 68.5% of the total volume of the Busan port. Due to this increase in volume, ultra large container ships call at Busan New Port. When the additional south container terminal as well as ongoing construction project of the west container terminal are completed, various encounters may occur at the Busan New Port entrance, which may cause collision risk.s Thus, the purpose of this study was to provide a plan to improve the safety of vessel traffic, in the in/out bound fairway of Busan New Port. For this purpose, the status of arrivals and departures of vessels in Busan New Port, was examined through maritime traffic flow analysis. Additionally, risk factors and safety measures were identified, by AHP analysis with ship operators of the study area. Also, based on the derived safety measures, scenarios were set using the Environmental Stress model (ES model), and the traffic risk level of each safety measure was identified through simulation. As a result, it is expected that setting the no entry area for one-way traffic would have a significant effect on mitigating risks at the Busan New Port entrance. This study can serve as a basis for preparing safety measures, to improve the navigation of vessels using Busan New Port. If safety measures are prepared in the future, it is necessary to verify the safety by using the traffic volume and flow changes according to the newly-opened berths.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.33-38
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• 2014

The FCM based hybrid RBF network is a heterogeneous learning network model that applies FCM algorithm between input and middle layer and applies Max_Min algorithm between middle layer and output. The Max-Min neural network uses winner nodes of the middle layer as input but shows inefficient learning in performance when the input vector consists of too many patterns. To overcome this problem, we propose a dynamic learning rate control based on fuzzy logic. The proposed method first classifies accurate/inaccurate class with respect to the difference between target value and output value with threshold and then fuzzy membership function and fuzzy decision logic is designed to control the learning rate dynamically. We apply this proposed RBF network to the character recognition problem and the efficacy of the proposed method is verified in the experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1898-1907
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• 2022

Every year, many shipping companies provide seaman safety education programs periodically to reduce ocean-traffic accidents. However, undertaking the regular safety training for seaman has been difficult because of litimation of space and time. Recently, VR technolgy is received attentions to overcome previous problems. It can provide users educational interactions between a user and virtual environment and fulfill sustainable teaching. In this paper, VR-based safety education content for sailors has been developed, and it includes four programs. Also, survey was conducted with four questionnaires such as immersiveness, easy to experience, satisfaction of education contents, comparative evaluation between traditional education program and VR education contents. As the result, immersiveness questionnaire could be gain 53.83% positive assessment, and easy to experience could be gain 65.38% positive assessment, and satisfaction could be gain 69.23% positive assessment. Lastly, comparative evaluation between traditional education program and VR education contents could be gain about 46% positive and 34% neutral assessments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.36-43
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• 2005

RFID(Radio Frequency IDentification: 라디오 주파수 인식)란 라디오 주파수를 활용해서 무선으로 사물을 인식하는 것을 의미한다. RFID 기술을 구성하는 기본 요소는 태그, 안테나, 리더 등이다. 본 연구에서는 이러한 RFID 기술의 기본 요소와 더불어 인식된 사물의 정보를 광범위하게 구축되어 있는 유${\cdot}$무선 네트워크와 연결하여 활용할 수 있는 모든 기술을 RFID 기술로 정의하였다. 비록 최근에 RFID 기술이 여러 분야에서 큰 이슈로 떠오르고 있지만, 실제 RFID 기술은 오래전인 2차 세계대전에 영국군의 자국 전투기 식별을 위해 이미 활용되고 있었다. 그러나 그 당시에는 RFID 기술의 구성요소인 태그나 리더의 값이 고가였기 때문에 특정분야에 한해 RFID 기술을 적용할 수 있었다. 그 이후에 1990년대에 이르러 RFID 기술은 가축관리, 컨테이너관리, IC 카드 등 점차 다른 분야로 적용이 확대되기 시작했다. 특히 반도체 기술의 발전이 급속도로 이루어진 1990년대 말을 기점으로 RFID 기술에 대한 연구가 활발히 이루어져, 현재에는 SCM(Supply Chain Management), 국방, 의료, 교통, 환경, 동물관리, 홈 네트워크 등 다양한 분야에 적용이 가능한 기술로 평가되고 있다. 특히, SCM에 있어서 RFID 기술 도입은 큰 파급효과가 예상되고 있다. SCM을 구성하는 기업들은 RFID 기술 도입을 통해 제품의 가시성(visibility)과 추적성(traceability)을 확보할 수 있게 된다. 기업들은 자신의 제품이 현재 어디에 있으며 어떠한 경로를 통해 그 자리에 이르렀는지를 실시간(real time)으로 확인 가능하게 된다. 미국의 월마트사(社) 와 영국의 메트로사(社) 같은 선진 유통 기업들은 실증연구를 통해 RFID 기술 도입이 비용 절감과 함께 고객 서비스 향상을 도모할 것이라는 결론을 내린 바 있다. 또한 현제 초기단계이기는 하지만 실제 RFID 기술을 도입하여 운영 중에 있다. 국내에서도 정부주도 하에 RFID 기술에 대한 연구가 활발하게 이루어지고 있으며, 지난 2004년에 유통 물류 분야의 1차 시범사업을 완료하였다. 그러나, 이러한 국내${\cdot}$외의 적극적인 도입 움직임에도 불구하고 국내에서는 아직 RFID기술 도입이 SCM(Supply Chain Management)에 있어서 구체적으로 어떠한 영향을 미치는가에 대한 연구가 거의 이루어지지 못하고 있는 실정이다. 특히 RFID 기술 도입 의사결정자에게 제공될 수 있는 정량적인 ROI 분석 모형에 관한 연구는 시급한 과제로 떠오르고 있다. 따라서 본 연구에서는 SCM 차원에서 RFID 기술 도입에 따른 ROI 분석 모형을 제시하고 적용해 보고자 한다.

• The Journal of the Korea Contents Association
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• v.17 no.7
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• pp.276-282
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• 2017

Password-based authentication is vulnerable because of its low cost and convenience, but it is still widely used. In order to increase the security of the password-based user authentication method, the password is changed frequently, and it is recommended to use a combination of numbers, alphabets and special characters when generating the password. However, it is difficult for users to remember passwords that are difficult to create and it is not easy to change passwords periodically. Therefore, in this paper, we implemented a user authentication system that does not require a password by using the USB memory that is commonly used. Authentication data used for authentication is protected by USB data stored in USB memory using USB device information to improve security. Also, the authentication data is one-time and reusable.Based on this, it is possible to have the same security as the password authentication system and the security level such as certificate or fingerprint recognition.