• The Korean Journal of Community Living Science
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• v.22 no.2
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• pp.247-255
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• 2011

This study analyzed the demand for a community-based tourism site using a poisson model, a negative binominal model, a truncated poisson model and a truncated negative binominal model as count data models. For these reasons, questionnaire surveys were conducted into 5 community-based tourism sites in Chuncheon city with 406 tourists, and was analyzed using the STATA program. The fitness levels of four models were significant(p=0.0000) using a likelihood ratio test. The study results suggest that the demand of community-based tourism sites for visiting tourists was influenced by a pre-visiting experience, recognition of sustainable tourism, visitation of downtown, purchase of souvenir or farm produce, conversation with regional residents, regional harmony, preservation of natural resources and sex within the poisson and truncated poisson models. However, the variables of visitation of downtown, preservation of natural resources and sex were not significant within the negative binominal model and the visitation of downtown and preservation of natural resources were not significant within the truncated negative binominal model. The results of the visiting demand of community-based tourism sites can provide information for sustainable regional development strategies.

• Journal of the Korean Society for Library and Information Science
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• v.54 no.3
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• pp.237-262
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• 2020

Part-time instructors are contributing to the production of excellent human resources through education and research, strengthening research competitiveness, and national and social knowledge and academic development. Therefore, academic and research information services for part-time instructors are essential for their educational and research activities. In this study, researcher suggested various methods for providing efficient educational and academic information services by surveying and analyzing their information environment, information needs, and educational and academic information recognition and usage behavior by applying the survey method to part-time instructors.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.992-1000
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• 2009

Available electric wave resources have been limited than frequency demands that increase with the development of radio communication. According to FCC's (Federal Communication Commission) report, 70% of allocated spectrum was unused. This means that the lack phenomenon of electronic wave resources is ineffectively managed compare with the finiteness of frequency resources. According to the recognition of unused frequency within allocated band, this progress has been investigating to identify the unused TV channel and provide radio communication services. This paper proposed the sensing algorithm that efficiently recognizes the frequency resources which does not use and shares with the licensed user through using the multi-band CIC (Cascaded Integrator Comb) filter based on polyphase filter bank. The simulation results verifies that the proposed scheme can obtain the similar performance of variance and relatively low complexity to the existing scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2155-2161
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• 2016

Since Korea is highly dependent on energy imports, it has been making efforts to save energy resources by enacting laws to promote resource saving and recycling. Recently, as a part of recycling of empty bottles, a bottle unattended collecting machine has been installed in the big shopping mall in the metropolitan area. However, there is no commercialization of the unattended collecting machine in Korea and the smart device application for providing information on empty bottle recycling is not yet provided. In this paper, we have designed and constructed a bottle recycling information management system to promote resource recycling. The manager has built a homepage that can manage the information of the empty bottle and the a bottle unattended collecting machine. Also, many people with smart devices can easily access bottle recycling information by using camera and barcode search and label search.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.651-654
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• 2021

Face anti-spoofing (FAS) techniques play a significant role in the defense of facial recognition systems against spoofing attacks. Existing FAS methods achieve the great performance depending on annotated additional modalities. However, labeling these high-cost modalities need a lot of manpower, device resources and time. In this work, we proposed to use self-transforming modalities instead the annotated modalities. Three different modalities based on frequency domain and temporal domain are applied and analyzed. Intuitive visualization analysis shows the advantages of each modality. Comprehensive experiments in both the CNN-based and transformer-based architecture with various modalities combination demonstrate that self-transforming modalities improve the vanilla network a lot. The codes are available at https://github.com/chenmou0410/FAS-Challenge2021.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.11
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• pp.87-104
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• 2015

Currently the IoT (Internet of Things) environments and related technologies are being developed rapidly through the networks for connecting many intelligent objects. The IoT is providing artificial intelligent services combined with context recognition based knowledge and communication methods between human and objects and objects to objects. With the help of IoT technology, many research works are being developed using the C-ITS (Cooperative Intelligent Transport System) which uses road infrastructure and traveling vehicles as traffic control infrastructures and resources for improving and increasing driver's convenience and safety through two way communication such as bus-only lane and license plate recognition and road accidents, works ahead reports, which are eventually for advancing traffic effectiveness. In this paper, a system for deciding whether the traveling vehicle is possible or not to drive on bus-only lane in highway is researched using the lane and number plate recognition on the road in C-ITS traffic infrastructure environments. The number plates of vehicles on the straight ahead and sides are identified after the location of bus-only lane is discovered through the lane recognition method. Research results and experimental outcomes are presented which are supposed to be used by traffic management infrastructure and controlling system in future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2764-2782
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• 2021

Existing city-level boundary nodes identification methods need to locate all IP addresses on the path to differentiate which IP is the boundary node. However, these methods are susceptible to time-delay, the accuracy of location information and other factors, and the resource consumption of locating all IPes is tremendous. To improve the recognition rate and reduce the locating cost, this paper proposes an algorithm for city-level boundary node identification based on bidirectional approaching. Different from the existing methods based on time-delay information and location results, the proposed algorithm uses topological analysis to construct a set of candidate boundary nodes and then identifies the boundary nodes. The proposed algorithm can identify the boundary of the target city network without high-precision location information and dramatically reduces resource consumption compared with the traditional algorithm. Meanwhile, it can label some errors in the existing IP address database. Based on 45,182,326 measurement results from Zhengzhou, Chengdu and Hangzhou in China and New York, Los Angeles and Dallas in the United States, the experimental results show that: The algorithm can accurately identify the city boundary nodes using only 20.33% location resources, and more than 80.29% of the boundary nodes can be mined with a precision of more than 70.73%.

• Journal of IKEEE
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• v.14 no.3
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• pp.224-231
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• 2010

Automatic detection of objects in images has been one of core challenges in the areas such as computer vision and pattern analysis. Especially, with the recent deployment of personal mobile devices such as smart phone, such technology is required to be transported to them. Usually, these smart phone users are equipped with devices such as camera, GPS, and gyroscope and provide various services through user-friendly interface. However, the smart phones fail to give excellent performance due to limited system resources. In this paper, we propose a new scheme to improve object recognition performance based on pre-computation and simple local features. In the pre-processing, we first find several representative parts from similar type objects and classify them. In addition, we extract features from each classified part and train them using regression functions. For a given query image, we first find candidate representative parts and compare them with trained information to recognize objects. Through experiments, we have shown that our proposed scheme can achieve resonable performance.

• Proceedings of the IEEK Conference
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• summer
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• pp.387-390
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• 2004

In this paper, we design and implement practical application service using VoiceXML. And we suggest new solutions of problems can be occurred when implementing a new systems using VoiceXML, based on the fact. Up to now, speech related services were developed using API (Application Program Interface) and programming languages, which methods depend on system architectures. It thus appears that reuse of contents and resource was very difficult. To solve these problems, nowadays, companies develop their applications using VoiceXML. Advantages of using VoiceXML when developing services are as follows. First, we can use web developing technologies and technologies for transmitting web contents. And, we can save labors for low level programming like C language or Assembler language. And we can save labors for managing resources, too. As the result of these advantages, we can reduce developing hours of applications services and we can solve problem of compatibility between systems. But, there's poor grip of actual problems can be occurred when implementing their own services using VoiceXML. To overcome these problems, we implemented interactive stock trading system using VoiceXML and concentrated our effort to find out problems when using VoiceXML. And then, we proposed solutions to these problems and analyzed strong points and weak points of suggested system.

• 한국어정보학회:학술대회논문집
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• 2017.10a
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• pp.143-146
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• 2017

심층학습 모델 중 LSTM-CRF는 개체명 인식, 품사 태깅과 같은 sequence labeling에서 우수한 성능을 보이고 있다. 한국어 개체명 인식에 대해서도 LSTM-CRF 모델을 기본 골격으로 단어, 형태소, 자모음, 품사, 기구축 사전 정보 등 다양한 정보와 외부 자원을 활용하여 성능을 높이는 연구가 진행되고 있다. 그러나 이런 방법은 언어 자원과 성능이 좋은 자연어 처리 모듈(형태소 세그먼트, 품사 태거 등)이 없으면 사용할 수 없다. 본 논문에서는 LSTM-CRF와 최소한의 언어 자원을 사용하여 다국어에 대한 개체명 인식에 대한 성능을 평가한다. LSTM-CRF의 입력은 문자 기반의 n-gram 표상으로, 성능 평가에는 unigram 표상과 bigram 표상을 사용했다. 한국어, 일본어, 중국어에 대해 개체명 인식 성능 평가를 한 결과 한국어의 경우 bigram을 사용했을 때 78.54%의 성능을, 일본어와 중국어는 unigram을 사용했을 때 각 63.2%, 26.65%의 성능을 보였다.