• 한국전기전자재료학회논문지
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• 제23권8호
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• pp.632-637
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• 2010

The measurement of contact wire wear in electric railways is one of the key test parameters to increase speed and maintain safety in electric railways. Wear caused by continuous interaction between pantographs and contact wires has a negative effect on current collection quality and severely damaged contact wires might cause hazardous accidents. This paper introduces a non-contact optical-based contact wire wear measuring system that will replace conventional wear detecting methods conducted by maintenance vehicles or workers. The system is implemented by high-speed cameras that can collect images of contact wires during vehicle operation, a laser used to create images profile of the contact wire surface, and a computer used to process the collected images. The proposed system is designed to assist maintenance of overhead contact lines by creating geometrically plotted images of contact wires to detect contact wire wear during operation on conventional lines or high-speed lines.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2009년도 하계학술대회 논문집
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• pp.460-461
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• 2009

We studied the effects of post-annealing treatment on poly(3-hexylthiophene)(P3HT, donor):[6,6]-phenyl $C_{61}$ butyric acid methyl ester(PCBM, acceptor) blend film as an active layer in the organic solar cells(OSCs). For the formation of the active layer, 3 wt.% P3HT:PCBM solution in chlorobenzene were deposited by spin-coating method. In order to optimize the performance of OSCs, the P3HT crystallization and the redistribution of PCBM cluster at P3HT:PCBM composition as a function of post-annealing condition from room temperature to $200^{\circ}C$ were measured by the Hall effect and the UV-vis Spectrophotometer. We thought that the improved efficiency in the OSCs with post-annealing treatment at $150^{\circ}C$ can be explained by the efficient separation or collection of the photogenerated excitons at donor-acceptor interface by P3HT crystallization.

• 한국전자통신학회논문지
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• 제15권5호
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• pp.959-966
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• 2020

수산업의 중요성이 커지고 양식 산업이 급성장한 가운데 수산 양식 분야 ICT 융합을 통한 스마트 양식장에 대한 연구가 진행되고 있다. 양식장 현장에서 생육 환경 모니터링이 가능하도록 수중 드론의 구동부, 영상 수집 장치, 자세 안정화를 위한 통합 컨트롤러, 실시간 수중 영상을 통한 드론 조정 및 제어가 가능한 원격 관제 장치를 제안하고 설계, 개발 및 시험을 진행하였다. 수중 드론 활용을 통해 양식 산업에서 문제 되는 인력 수급 및 고비용 작업을 대체 할 수 있으며, 양식 폐사 확률을 줄여 안정적인 양식장 관리가 가능하다.

• 전기학회논문지
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• 제66권9호
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• pp.1402-1408
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• 2017

Recently, services for personal biometric data analysis based on real-time monitoring systems has been increasing and many of them have focused on recognition of emotions. In this paper, we propose a classification model to classify anxiety emotion using biometric data actually collected from people. We propose to deploy the support vector machine to build a classification model. In order to improve the classification accuracy, we propose two data pre-processing procedures, which are normalization and data deletion. The proposed algorithms are actually implemented based on Real-time Traffic Flow Measurement structure, which consists of data collection module, data preprocessing module, and creating classification model module. Our experiment results show that the proposed classification model can infers anxiety emotions of people with the accuracy of 65.18%. Moreover, the proposed model with the proposed pre-processing techniques shows the improved accuracy, which is 78.77%. Therefore, we can conclude that the proposed classification model based on the pre-processing process can improve the classification accuracy with lower computation complexity.

• 한국도서관정보학회지
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• 제34권4호
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• pp.83-103
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• 2003

전자책이 우리 주변에서 점차 소개되면서 읽기 습관에도 영향을 끼치고 있다. 전자책의 내용은 시간과 공간을 초월하여 개인용 컴퓨터나 전자책 가독기를 통하여 언제나 접근할 수 있는 가능성을 제공하는 것 등 긍정적인 면이 있다. 이와 같은 상당한 기대와 관심에도 불구하고 전자책 등장 당시 우리가 기대한 것만큼은 활성화되기 못하고 있는 실정이다. 본 연구는 어떠한 비즈니스 모델이나 하드웨어, 소프트웨어 표준이 전자책 시장을 활성화하고 도서관 서비스를 충족시킬 수 있을 것인가에 대하여, 전자책 시장을 둘러싼 현재의 환경을 조사하고, 이를 바탕으로 전자책이 좀 더 활용될 수 있는 가이드라인을 제시하고자 하였다. 본 연구를 통하여 얻은 선진국에서의 전자책 시장과 기술 그리고 도서관에서의 경험적 사례와 논점 등은 우리나라 도서관계와 출판계에 귀중한 교훈을 제시할 수 있을 것이다.

• 정보관리학회지
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• 제20권3호
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• pp.261-276
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• 2003

시민의 정보화 수준 향상을 위해 현재 서울특별시립의 공공도서관에서는 디지털 자료실을 개실하여 인터넷과 DVD 위성방송 등 다양한 전자정보원과 정보서비스를 제공하고 있으며 향후 더 많은 컨텐츠들로 서비스 할 계획이다. 이에 따라 본 연구에서는 서울특별시립 공공도서관 디지털 자료실의 활성화를 위해, S 도서관 전자정보실을 대상으로 마케팅 전략을 적용하여 디지털 자료실의 운영을 보다 체계화하여 정보서비스를 활성화하며, 궁극적으로 보다 많은 이용자를 확보하여, 이용률을 높이고 공공도서관의 정보서비스 경쟁력을 높이는 방안을 제시하고자 하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2007년도 춘계종합학술대회
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• pp.611-614
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• 2007

본 논문은 PDA(Personal Digital Assistant)와 WLAN(Wireless Local Area Network) 기술을 결합한 TCP-IP 통신 기반의 원격 장치 데이터 모니터링 시스템을 제안한다. 무선의 PDA 디바이스는 서버측에서 전송되는 원격 장치의 데이터인 온도, 습도, 장치 상태 등을 연속적으로 수집하고 모바일 디바이스에 디스플레이 함으로써 무선 통신의 원격 모니터링을 위해서 사용된다. 따라서 유 무선 통합의 원격 장치 데이터 모니터링 시스템을 구축함으로써 관리자의 상황에 적응적인 데이터 수집과 장치 상태 확인의 효율성을 제공한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 제36회 하계학술대회 논문집 D
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• pp.2888-2890
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• 2005

In this paper, we introduce a new structure of fuzzy-neural networks Fuzzy Set-based Polynomial Neural Networks (FSPNN). The two underlying design mechanisms of such networks involve genetic optimization and information granulation. The resulting constructs are Fuzzy Polynomial Neural Networks (FPNN) with fuzzy set-based polynomial neurons (FSPNs) regarded as their generic processing elements. First, we introduce a comprehensive design methodology (viz. a genetic optimization using Genetic Algorithms) to determine the optimal structure of the FSPNNs. This methodology hinges on the extended Group Method of Data Handling (GMDH) and fuzzy set-based rules. It concerns FSPNN-related parameters such as the number of input variables, the order of the polynomial, the number of membership functions, and a collection of a specific subset of input variables realized through the mechanism of genetic optimization. Second, the fuzzy rules used in the networks exploit the notion of information granules defined over systems variables and formed through the process of information granulation. This granulation is realized with the aid of the hard C- Means clustering (HCM). The performance of the network is quantified through experimentation in which we use a number of modeling benchmarks already experimented with in the realm of fuzzy or neurofuzzy modeling.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.1505-1509
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• 2005

This paper introduces a new architecture of genetically optimized self-organizing fuzzy polynomial neural networks by means of information granulation. The conventional SOFPNNs developed so far are based on mechanisms of self-organization and evolutionary optimization. The augmented genetically optimized SOFPNN using Information Granulation (namely IG_gSOFPNN) results in a structurally and parametrically optimized model and comes with a higher level of flexibility in comparison to the one we encounter in the conventional FPNN. With the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The GA-based design procedure being applied at each layer of genetically optimized self-organizing fuzzy polynomial neural networks leads to the selection of preferred nodes with specific local characteristics (such as the number of input variables, the order of the polynomial, a collection of the specific subset of input variables, and the number of membership function) available within the network. To evaluate the performance of the IG_gSOFPNN, the model is experimented with using gas furnace process data. A comparative analysis shows that the proposed IG_gSOFPNN is model with higher accuracy as well as more superb predictive capability than intelligent models presented previously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1595-1613
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• 2017

The IR camera and laser-based IR projector provide an effective solution for real-time collection of moving targets in RGB-D videos. Different from the traditional RGB videos, the captured depth videos are not affected by the illumination variation. In this paper, we propose a novel feature extraction framework to describe human activities based on the above optical video capturing method, namely spatial-temporal texture features for 3D human activity recognition. Spatial-temporal texture feature with depth information is insensitive to illumination and occlusions, and efficient for fine-motion description. The framework of our proposed algorithm begins with video acquisition based on laser projection, video preprocessing with visual background extraction and obtains spatial-temporal key images. Then, the texture features encoded from key images are used to generate discriminative features for human activity information. The experimental results based on the different databases and practical scenarios demonstrate the effectiveness of our proposed algorithm for the large-scale data sets.