• 한국환경과학회지
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• 제11권6호
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• pp.463-470
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• 2002

Environmental protection and precaution are the most frequently considered issues in the recent research fields for our present and future surroundings. However, it seems that these environmental issues were less reflected in local-level development plans, and caused several cases of environmental pollution, therefore it became a major concern of local governments and the communities. The role of a 'Local EIA(Environment Impact Assessment)' can be a core issue for the positive preferences of the local-level development plans. Cases of Local EIA in Germany which have been implied successfully are reviewed to generate a local EIA movement and to produce a guideline for Korean local governments. The local EIA in Germany was broadly commenced in the middle of 1980s, and a decade later it was carried out for over 200 of local governments. To produce a better suggestion for Korean local EIA, comparison and analysis of detail data of the German local EIA was carried out, and tested for fourteen cities in Korea based on five categories: i) assessment subject, ii) assessment procedure, iii) main office for assessment, iv) assessment factor and v) assessment standard. Prior suggestions for greater preference of local EIA in Korea are: it is necessary that I) launch of a support system in central government to help the movement of local government; Ⅱ) a knowledge-based expert group in local government which has by all means of exclusive responsibility far any action(new application or performance of local EIA) : 111) establishment of 'environmental protection measure' in local government level for environmental precaution based on individual environmental character and values in their communities.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.3972-3988
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• 2020

Existing methods always rely on statistical features to extract local words for microblog user geolocation. There are many non-local words in extracted words, which makes geolocation accuracy lower. Considering the statistical and semantic features of local words, this paper proposes a microblog user geolocation method by extracting local words based on word clustering and wrapper feature selection. First, ordinary words without positional indications are initially filtered based on statistical features. Second, a word clustering algorithm based on word vectors is proposed. The remaining semantically similar words are clustered together based on the distance of word vectors with semantic meanings. Next, a wrapper feature selection algorithm based on sequential backward subset search is proposed. The cluster subset with the best geolocation effect is selected. Words in selected cluster subset are extracted as local words. Finally, the Naive Bayes classifier is trained based on local words to geolocate the microblog user. The proposed method is validated based on two different types of microblog data - Twitter and Weibo. The results show that the proposed method outperforms existing two typical methods based on statistical features in terms of accuracy, precision, recall, and F1-score.

• 인터넷정보학회논문지
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• 제21권2호
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• pp.57-64
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• 2020

The widespread use of smartphones with a variety of features has enabled mobile Internet-based services. One of these is online-to-offline (O2O) based services that connects online users with offline stores to add value. Applying this O2O strategy to local information retrieval induces online users to be linked to offline regions, thereby enabling the exchange of local-based information and helps create new value. This paper proposes and illustrates the implementation of O2O-based a local information providing service that utilizes photos of the local attraction. Also, we propose a fake-free ranking method to provide reliable local information to users and suggest its application of the service.

• Journal of Electrical Engineering and Technology
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• 제4권2호
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• pp.149-158
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• 2009

It is important to derive reliable parameter values in the measurement-based load model development of electric power systems. However parameter estimation tasks, in practice, often face the parameter identifiability issue; whether or not the model parameters can be estimated with a given input-output data set in reliable manner. This paper introduces concepts and practical definitions of the local identifiability of model parameters. A posteriori local identifiability is defined in the sense of nonlinear least squares. As numerical examples, local identifiability of third-order induction motor (IM) model and a Z-induction motor (Z-IM) model is studied. It is shown that parameter ill-conditioning can significantly affect on reliable parameter estimation task. Numerical studies show that local identifiability can be quite sensitive to input data and a given local solution. Finally, several countermeasures are proposed to overcome ill-conditioning problem in measurement-based load modeling.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1997년도 Proceedings International Workshop on New Video Media Technology
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• pp.113-118
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• 1997

This paper proposes a object tracking method based on the local moments, or moment based on the local moments, or moment of some restricted area, in which the idea of the viewpoint and the visual filed corresponding to the local area of an image is introduced. Using local moment with the optimally controlled viewpoint and visual field, the target position and its breadth are estimated robustly. By two experiments, the validity of the proposed method is shown.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2006년도 하계학술대회
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• pp.251-257
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• 2006

The performance of face recognition methods using subspace projection is directly related to the characteristics of their basis images, especially in the cases of local distortion or partial occlusion. In order for a subspace projection method to be robust to local distortion and partial occlusion, the basis images generated by the method should exhibit a part-based local representation. We propose an effective part-based local representation method named locally salient ICA (LS-ICA) method for face recognition that is robust to local distortion and partial occlusion. The LS-ICA method only employs locally salient information from important facial parts in order to maximize the benefit of applying the idea of 'recognition by parts.' It creates part-based local basis images by imposing additional localization constraint in the process of computing ICA architecture I basis images. We have contrasted the LS-ICA method with other part-based representations such as LNMF (Localized Non-negative Matrix Factorization)and LFA (Local Feature Analysis). Experimental results show that the LS-ICA method performs better than PCA, ICA architecture I, ICA architecture II, LFA, and LNMF methods, especially in the cases of partial occlusions and local distortion

• 아태비즈니스연구
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• 제10권1호
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• pp.135-147
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• 2019

Despite the importance of multinational service ventures' alliances with local firms for CSR engagement, research is little interested in this issue. Because many multinational service ventures have increasingly allied with local firms for their CSR performance, it is important to explain the role of the alliance between a multinational service venture and a local firm. Our study addressed an issue of multinational service ventures' CSR performance through alliances with local firms. Based prominently on the resource-based theory of the firm, the competence-based theory of the firm, and the resource-adavantage theory of competition, we attempted to predict how a multinational service venture can be successful in CSR engagement based on an alliance with a local firm. Our study posited that local firms' CSR knowledge and CSR orientation positively influence multinational service ventures's CSR capabilities. In addition, we posited the positive moderating roles of alliance competence in the relationships between local firms' CSR resources and multinational service ventures' CSR capability. Moreover, our study posited that multinational service ventures' CSR capability is a source of competitive advantage. Finally, we concluded this manuscript with a discussion of scholarly and managerial implications, limitations of the study, and directions for a further study.

• Journal of Forest and Environmental Science
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• 제35권2호
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• pp.102-114
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• 2019

The issue of sustainable forest management (SFM) continues to emerge as part of the REDD+ mechanism mitigation efforts. Especially for some developing countries, such as Indonesia, forest management is required to provide benefits to the welfare of local communities in addition to forest conservation efforts. This study aims to identify the economic, social, and environmental impacts of community-based forest management (CBFM) implementation activities, which is one of the implementations of SFM at field level. The primary objectives were to find out the impacts of CBFM activities based on local people's perceptions and to identify what factors need to be considered to increase local people's satisfaction on CBFM activities. The data from 6 sub-villages was derived through surveys with local people involved in CBFM activities, interviews with a key informant, and supported by secondary data. The results of the study state that CBFM activities have increased the local people's income as well as their welfare, strengthening the local institution, and help to resolve conflicts in the study area. CBFM has also been successful in protecting forests by rehabilitating unproductive lands and increase forest cover area. By using binary logistic regression analysis, it found that income, business development opportunities, access to forests, conflict resolution, institutional strengthening, and forest rehabilitation variable significantly affected the local people's satisfaction of CBFM activities.

• 대한전자공학회논문지SP
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• 제47권3호
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• pp.54-60
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• 2010

얼굴 인식 방법 중에 한 얼굴 영상을 분할하여 분할한 각 부분마다 통계적 방법을 적용해 특징추출을 수행한 다음 각 부분마다 분류를 수행하고 이러한 분류결과를 모아서 voting등의 방법으로 얼굴 인식을 수행 하는 방법을 국부 외형 기반 방법(local appearance-based method) 이라고 한다. 기존에 제안된 국부 외형 기반 얼굴 인식은 얼굴 영상을 일정한 크기로 단순분할하고, 그 부분들을 모두 인식에 사용한다. 본고에서는 인식에 상대적으로 중요한 부분만을 사용하여 얼굴 인식을 수행하는 새로운 국부 외형 기반 얼굴 인식 방법을 제안한다. 본고에서는 단순 분할 방법 대신에 눈, 코, 입 등 인물 간의 차이가 잘 나타나는 얼굴 부분들을 support vector machine (SVM) 을 이용하여 검출한 후, 검출한 각 부분에 주성분 분석 (PCA) 을 적용하고 이를 통합하여 얼굴 인식을 수행하였다. 실험을 통해 제안한 방법과 기존 방법의 성능을 비교한 결과, 제안한 방법이 기존의 국부 외형 기반 방법의 장점을 지니는 동시에 성능을 개선시킴을 확인하였다.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제18권2호
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• pp.129-142
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• 2014

We propose a variational segmentation model based on statistical information of intensities in an image. The model consists of both a local region-based energy and a global region-based energy in order to handle misclassification which happens in a typical statistical variational model with an assumption that an image is a mixture of two Gaussian distributions. We find local ambiguous regions where misclassification might happen due to a small difference between two Gaussian distributions. Based on statistical information restricted to the local ambiguous regions, we design a local region-based energy in order to reduce the misclassification. We suggest an algorithm to avoid the difficulty of the Euler-Lagrange equations of the proposed variational model.