• Journal of Korea Multimedia Society
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• v.24 no.2
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• pp.245-254
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• 2021

We proposed the research on an analysis and prediction model that allows the identification of outliers or abnormality in the data followed by effective and rapid imputation of missing values was conducted. This model is expected to analyze efficiently the problems in the data based on the calibrated raw data. As a result, a system that can adequately utilize the data was constructed by using the introduced KNN + MLE algorithm. With this algorithm, the problems in some of the existing KNN-based missing data imputation algorithms such as ignoring the missing values in some data sections or discarding normal observations were effectively addressed. A comparative evaluation was performed between the existing imputation approaches such as K-means, KNN, MEI, and MI as well as the data missing mechanisms including MCAR, MAR, and NI to check the effectiveness/efficiency of the proposed algorithm, and its superiority in all aspects was confirmed.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.435-446
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• 2022

Identifying ship types is an important process to prevent illegal activities on territorial waters and assess marine traffic of Vessel Traffic Services Officer (VTSO). However, the Terrestrial Automatic Identification System (T-AIS) collected at the ground station has over 50% of vessels that do not contain the ship type information. Therefore, this study proposes a method of identifying ship types through the Random Forest Classifier (RFC) from dynamic and static data of AIS and V-Pass for one year and the Ulsan waters. With the hypothesis that six features, the speed, course, length, breadth, time, and location, enable to estimate of the ship type, four classification models were generated depending on length or breadth information since 81.9% of ships fully contain the two information. The accuracy were average 96.4% and 77.4% in the presence and absence of size information. The result shows that the proposed method is adaptable to identifying ship types.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.06a
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• pp.302-303
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• 2022

자율운항선박의 시대 도입을 위해 보안체계의 중요성은 더욱 커져가고 있다. 국내 및 국외 학계에서는 해양선박 보안에 관한 연구가 활발히 이루어지고 있는데 자율운항선박은 자율운행자동차와 마찬가지로 주위 환경에 대한 자동식별장치가 필요하다. 선박자동식별장치(Automatic Identification System, AIS)는 선박의 종류와 위치 관련 데이터와 인증서를 포함한 정보를 인근의 항로표지로 전달한다. 인간이 개입하지 않는 자율운항 개발 단계에서는 사용자 인증이 더욱더 중요하며, 본 논문에서는 기존 사용자 인증방식에 대한 취약점을 보완할 블록체인을 기반한 사용자 인증 시스템을 연구하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.21-22
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• 2023

입항 수역이 좁은 제주항만은 단일 방향 통항이 가능한 one-way 방식을 사용 중 이다. 이러한 항만 특성으로 인해 제주항을 입출항 하는 선박들은 해상교통관제사(Vessel Traffic Service, VTS)의 지시에 의거하여 순서대로 입출항을 하고 있다. 본 연구는 VTS 관제사가 객관적이고 정확한 예측을 위해 선박자동식별장치(Automatic Identification System, AIS) 선박항적데이터를 이용하여 제주항에 입출항 하는 선박의 이동시간 통계를 산출하여 선박입출항 소요시간을 분석하고자 한다. 이를 위해 AIS 데이터를 이용하여 선박 이동시간을 산출하는 알고리즘을 제안하고, 이에 더하여 기상 상태와 항만 예선 사용에 따른 입출항 소요 시간을 취합하여 분석하고자 한다. 이에 따른 결과를 실제 관제에 적용 시켜 보다 더 안전하고 효율적으로 항만을 운영하는데 의의를 두고 있다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.181-182
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• 2021

본 연구에서는 자율운항선박의 원격 관제 및 제어하는 과정에서 원격 운항자에게 사전 충돌 위험 정보를 제공하기 위해 선박자동식별시스템(AIS, Automatic Identification System)의 항적 정보를 토대로 자율운항선박의 운항 경로 상에 잠재된 충돌 위험 영역을 예측하기 위한 기초 연구를 수행하였다. 자율운항선박의 운항 경로 상에 근접한 타선의 AIS 정보에는 기본적으로 선박의 위치, 속도, 침로에 대한 정보가 반영되어 있으므로, 이러한 정보를 토대로 일정 시간 동안 운항 경로를 예측할 수 있다. 그리고 예측한 정보를 기반으로 대표적 충돌 위험 지수인 최근접점(CPA, Closest Point of Approach)과 최근접점 거리(DCPA, Distance to CPA) 정보를 활용하여 충돌 위험 영역을 2차원 공간상에서 예측하였다. 제안된 방법은 실제 AIS 항적 데이터를 활용한 수치 시뮬레이션을 수행하여 초기 결과를 검증하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.4 s.310
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• pp.46-54
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• 2006

Recently, the important of a personal identification is increasing according to expansion using each on-line commercial transaction and personal ID-card. Although a personal ID-card embedded RFID(Radio Frequency Identification) tag is gradually increased, the way for a person's identification is deficiency. So we need automatic methods. Because RFID tag is vary small storage capacity of memory, it needs effective feature extraction method to store personal biometrics information. We need new recognition method to compare each feature. In this paper, we studied the face verification system using Hippocampal neuron modeling algorithm which can remodel the hippocampal neuron as a principle of a man's brain in engineering, then it can learn the feature vector of the face images very fast. and construct the optimized feature each image. The system is composed of two parts mainly. One is feature extraction using NMF(Non-negative Matrix Factorization) and LDA(Linear Discriminants Analysis) mixture algorithm and the other is hippocampal neuron modeling and recognition simulation experiments confirm the each recognition rate, that are face changes, pose changes and low-level quality image. The results of experiments, we can compare a feature extraction and learning method proposed in this paper of any other methods, and we can confirm that the proposed method is superior to the existing method.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.95-110
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• 2006

To enhance the rule-based reasoning capability of Semantic Web, the XRML (eXtensible Rule Markup Language) approach embraces the meta-information necessary for the extraction of explicit rules from Web pages and its maintenance. To effectuate the automatic identification of rules from unstructured texts, this research develops a framework of using rule ontology. The ontology can be acquired from a similar site first, and then can be used for multiple sites in the same domain. The procedure of ontology-based rule identification is regarded as a graph search problem with incomplete nodes, and an A* algorithm is devised to solve the problem. The procedure is demonstrated with the domain of shipping rates and return policy comparison portal, which needs rule based reasoning capability to answer the customer's inquiries. An example ontology is created from Amazon.com, and is applied to the many online retailers in the same domain. The experimental result shows a high performance of this approach.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.107-115
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• 2010

RFID (Radio Frequency IDentification) technology, automatic identification and data capture technologies in ubiquitous computing is an essential skill. Low-cost Radio Frequency Identification tags using memory and no physical contact due to the ease of use and maintenance of excellence are going to use expanded. However, it is possible to the illegal acquisition of the information between RFID tags and readers because RFID uses the RF signal, and the obtained information can be used for the purpose of location tracking and invasion of privacy. In this paper, we proposed the security scheme to protect against the illegal user location tracking and invasion of privacy. The security scheme proposed in this paper, using Gray Code and reduced the capacity of the calculation of the actual tags, However, it is impossible for the malicious attacker to track information because tag information transmitted from the reader is not fixed. Therefore, even if the tags information is obtained by a malicious way, our scheme provides more simple and safe user privacy than any other protection methods to protect user privacy, because not actual information but encrypted information is becoming exposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.95-98
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• 2009

RFID(Radio Frequency IDentification) technology is an automatic identification method using radio frequencies between RFID reader which collects the informatin and tag which transmits the information. RFID technology develops passive RFID which transmit the only ID to active RFID which transmit the additional information such as sensing information. there is ISO/IEC 18000-7 as typical standard of active RFID. it is single channel system of 433.92MHz and has limitation of collection of a number of tags. to overcome limitation of collection of many tags, we propose the new 2.4GHz active RFID technology which can use the multi-channel. if reader has multi-interface and uses another channel in each, reader could fast collect the tags. but, if a reader which has many interfaces collects tags through the specific interface, the performance may not improve any more comparing with a reader using single interface. in this paper, we show the fast collection through design and implementation of protocol for load balancing between interfaces in multi-interface RFID reader.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.139-142
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• 2009

RFID(Radio Frequency IDentification) technology is an automatic identification method using radio frequencies between RFID reader which collects the information and tag which transmits the information. RFID technology develops passive RFID which transmit the only ID to active RFID which transmit the additional information such as sensing information. However, ISO/IEC 18000-7 as active RFID standard has a problem which cannot use multiple channel. To solve this problem, we use the 2.4GHz bandwidth technology and we propose the dynamic channel allocation method which can efficiently allot a channel. we show the operation of the dynamic channel allocation method through design and implement with CC2500DK of Taxas Instrument.