• Journal of Korean Library and Information Science Society
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• v.43 no.4
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• pp.113-137
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• 2012

This study aims to provide marketing strategies for the public libraries in Korea. For this purpose, this study focused on four public libraries in New York, USA, which have been providing the most excellent library services on the world. And this study examined what efforts these libraries have been making for the development of community and information needs of customers. The data for this study were collected by literature review, participant observation at the public libraries in New York, and gathering law materials. And in-depth interviews with the librarians and related professionals in New York and Korea were also proceeded. As a result, this study suggested marketing strategies for the management of public libraries in Korea.

• International Journal of Contents
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• v.11 no.2
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• pp.1-8
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• 2015

In this paper, we describe a novel method for document layout analysis that is based on a Fuzzy Energy Matrix (FEM). A FEM is a two-dimensional matrix that contains the likelihood of text and non-text and is generated through the use of Fuzzy theory. The key idea is to define an Energy map for the document to categorize text and non-text. The proposed mechanism is designed for execution with a low-resolution document image, and hence our method has a fast processing speed. The proposed method has been tested on public ICDAR 2009 datasets to conduct a comparison against other state-of-the-art methods, and it was also tested with Korean documents. The results of the experiment indicate that this scheme achieves superior segmentation accuracy, in terms of both precision and recall, and also requires less time for computation than other state-of-the-art document image analysis methods.

• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.215-224
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• 2012

This study performs an exploratory investigation of the needs of the customers who use academic information service from a research institute, K, that provides information services for domestic academic institutions of natural science and technology. K institute is planning customized services in order to improve customer satisfaction on the academic information service And therefore, the institute begins the research on customer needs analysis and customer segmentation. The research is regarded as well-timed, because CRM implementation in public organizations has been activated recently. Data mining and data warehousing techniques were used for pilot analyses. For the purpose of customer segmentation, a mixed segmentation model, which adds product life cycle concept to the 'balanced customer segmentation' model, which in turn considers the value of customers from the organizational viewpoint and the value of organizations from the customer's viewpoint, simultaneously, was applied. The result of investigation indicated that, in the case of K, 'balanced customer segmentation' and 'contents reach approach' which uses data warehouse/OLAP, rather than those customer segmentation techniques that are often used within the industry, are the more potent ways of approach. This exploratory case study is expected to provide a useful guideline for 'deriving an organizationally unique CRM model' that recently is one of the hot topics in the CRM area.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.549-558
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• 2021

In order to keep infrastructures such as tunnels and underground facilities safe, cracks of concrete lining in tunnel should be detected by regular inspections. Since regular inspections are accomplished through manual efforts using maintenance lift vehicles, it brings about traffic jam, exposes works to dangerous circumstances, and deteriorates consistency of crack inspection data. This study aims to provide methodology to automatically extract cracks from tunnel concrete lining images generated by the existing tunnel image acquisition system. Specifically, we train a deep learning based semantic segmentation model with open dataset, and evaluate its performance with the dataset from the existing tunnel image acquisition system. In particular, we compare the model performance in case of using all of a public dataset, subset of the public dataset which are related to tunnel surfaces, and the tunnel-related subset with negative examples. As a result, the model trained using the tunnel-related subset with negative examples reached the best performance. In the future, we expect that this research can be used for planning efficient model training strategy for crack detection.

• Journal of the Korean Society for Railway
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• v.16 no.5
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• pp.439-446
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• 2013

The market taxonomy approach may lead to the most effective strategy to promote the export of Korean Railway Systems. By prioritizing opportunities in the global marketplace and subsequently identifying market segments, this approach will reveal the most effective market strategies for Korean rail exporters. This study suggests the market potential index. In addition, it also introduces how market segmentation should be done for the global rail supply market. Applying the market taxonomy to derive strategic implications, this study portrays several export projects currently being undertaken by the Korean rail industry.

• Proceedings of the KSRS Conference
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• v.2
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• pp.647-650
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• 2006

Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery was acquired over the Little Miami River Watershed (1756 square miles) in Ohio, U.S.A., which is one of the largest hyperspectral image acquisition. For the development of a 4m-resolution land cover dataset, a hierarchical approach was employed using two different classification algorithms: 'Image Object Segmentation' for level-1 and 'Spectral Angle Mapper' for level-2. This classification scheme was developed to overcome the spectral inseparability of urban and rural features and to deal with radiometric distortions due to cross-track illumination. The land cover class members were lentic, lotic, forest, corn, soybean, wheat, dry herbaceous, grass, urban barren, rural barren, urban/built, and unclassified. The final phase of processing was completed after an extensive Quality Assurance and Quality Control (QA/QC) phase. With respect to the eleven land cover class members, the overall accuracy with a total of 902 reference points was 83.9% at 4m resolution. The dataset is available for public research, and applications of this product will represent an improvement over more commonly utilized data of coarser spatial resolution such as National Land Cover Data (NLCD).

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.29-36
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• 2011

The main purpose of this paper is to make a map showing canopy cover by using airborne Lidar data based on region. Watershed algorithm was applied to elevation data to conduct segmentation, and then canopy cover was estimated through the regions extracted. In the process of transforming point data to raster, we solved the problems about overestimation and underestimation by using frequency method. Also, canopy cover map could be produced with various scales by differing level of segmentation and it provides more accurate and precise information than ones of ordinary public forest map.

• Journal of Korean Society of Transportation
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• v.36 no.2
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• pp.129-140
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• 2018

In this study, we analyzed the electric vehicle (EV) purchasing behavior with market segmentation in Seoul using the binary logit model. For the model estimation, the experimental design of SP survey generated 24 scenarios with purchase price, charging station availability, and driving range of EVs. The results of market segmentation analysis indicated that the owners of subcompact and compact size cars were primarily affected by the purchasing price while those of mid and full size cars were more sensitive to the charging station availability. By housing type, the charging station availability was the most important factor for the residents of apartment while the purchase price was the most important factor to choose the EVs. These results presented that the EV supply strategy of the automobile manufacturer should be diversified according to the marketing target and the expansion of the public charging infrastructure should be the top priority in the government policy.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.375-381
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• 2016

Recently, a foreground-background segmentation using codebook model has been researched actively. The codebook is created one for each pixel in the image. The codewords are vector-quantized representative values of same positional training samples from the input image sequences. The training is necessary for a long time in the most of codebook-based algorithms. In this paper, the initial codebook model is generated simply using median operation with several image frames. The initial codebook is updated to adapt the dynamic changes of backgrounds based on the frequencies of codewords that matched to input pixel during the detection process. We implemented the proposed algorithm in the environment of visual c++ with opencv 3.0, and tested to some of the public video sequences from PETS2009. The test sequences contain the various scenarios including quasi-periodic motion images, loitering objects in the local area for a short time, etc. The experimental results show that the proposed algorithm has good performance compared to the GMM algorithm and standard codebook algorithm.

• Korean Business Review
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• v.11
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• pp.149-171
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• 1998

The most important thing in the Tourist Market Segmentation is to find descriptive variables which can describe the changes of tourist demand properly. There are many descriptive variables. Among them, vital statistical variables were proved to be effective. The strongest variable but which was studied much less is the Family Life Cycle. This study will focus on the relation between Family Life Cycle and Travel Behavior of Destination Choice. In this study, I will verify the validity of Family Life Cycle as a descriptive variable of Tourist Market Segmentation, and try to find the meaningful variable at each steps. Therefore, The purpose of this study is to explain the relation between Family Life Cycle and Travel Behavior of Destination Choice, to verify the validity of Family Life Cycle as descriptive variable and to find the strategy to respond to the increase in quantity and diversity of quality of Tourist Market. The studies on the Family Life Cycle should be updated continuously according to the change of family structure and it should be understood as standard for Tourist Market Segmentation in the public and private sphere.