• Health Policy and Management
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• v.12 no.2
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• pp.1-22
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• 2002

Since the early 1980s scholars have applied latent structure and other type of finite mixture models from various academic fields. Although the merits of finite mixture model are well documented, the attempt to apply the mixture model to medical service has been relatively rare. The researchers aim to try to fill this gap by introducing finite mixture model and segmenting inpatients DB from one general hospital. In section 2 finite mixture models are compared with clustering, chi-square analysis, and discriminant analysis based on Wedel and Kamakura(2000)'s segmentation methodology schemata. The mixture model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture model is to unfix the sample, to Identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. In section 3 and 4 we illustrate results of segmenting 4510 patients data including menial and ratio scales. And then, we show AHP can be identify the attractiveness of each segment, in which the decision maker can select the best target segment.

• Journal of the Optical Society of Korea
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• v.19 no.2
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• pp.149-153
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• 2015

A digital micro-mirror device (DMD) has the potential to modulate an incident wave with high speed, and the application for holographic display has been studied by many researchers. However, the quality of reconstructed image isn't good in comparison with that from a gray-scale amplitude-only hologram since it is a binary amplitude-only spatial light modulator (SLM). In this paper, we suggest a method generating a set of binary holograms to improve the quality of the reconstructed image. Here, we are concerned with the case for which the object plane is positioned at the Fourier domain of the plane of the SLM. In this case, any point in the Fourier plane is related to all points in the hologram. So there is a chance to generate a set of binary holograms illuminated by incident wave with constant optical power. Moreover, we find an interesting fact that the quality of reconstructed image is improved when the spatial frequency bandwidth of the binary hologram is limited. Therefore, we propose an iterative segmentation algorithm generating a set of binary holograms that are designed to be illuminated by the wave with constant optical power. The feasibility of our method is experimentally confirmed with a DMD.

• The Journal of the Acoustical Society of Korea
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• v.24 no.5
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• pp.262-270
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• 2005

In this paper, a new temporal decomposition method is proposed. where not oniy distortion but also entropy are involved in segmentation. The interpolation functions and the target feature vectors are determined by a dynamic Programing technique. where both distortion and entropy are simultaneously minimized. The interpolation functions are built by using a training speech corpus. An iterative method. where segmentation and estimation are iteratively performed. finds the locally optimum Points in the sense of minimizing both distortion and entropy. Simulation results -3how that in terms of both distortion and entropy. the Proposed temporal decomposition method Produced superior results to the conventional split vector-quantization method which is widely employed in the current speech coding methods. According to the results from the subjective listening test, the Proposed method reveals superior Performance in terms of qualify. comparing to the Previous vector quantization method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4907-4913
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• 2011

The purpose of this study is to find how the preferred properties of potential users for the outdoor space of the multi-family housing complex had changed according to time differance and to select the target market through market segmentation. The study has identified that the most important property among four properties had been changed from a Communication to a Amenity according to time difference. This is shown that considering information and communication as an important properties had been changed to regarding leisure and culture facilities as valuable properties.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1778-1797
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• 2021

Document image binarization is an important pre-processing step in document analysis and archiving. The state-of-the-art models for document image binarization are variants of encoder-decoder architectures, such as FCN (fully convolutional network) and U-Net. Despite their success, they still suffer from three limitations: (1) reduced feature map resolution due to consecutive strided pooling or convolutions, (2) multiple scales of target objects, and (3) reduced localization accuracy due to the built-in invariance of deep convolutional neural networks (DCNNs). To overcome these three challenges, we propose an improved semantic segmentation model, referred to as DP-LinkNet, which adopts the D-LinkNet architecture as its backbone, with the proposed hybrid dilated convolution (HDC) and spatial pyramid pooling (SPP) modules between the encoder and the decoder. Extensive experiments are conducted on recent document image binarization competition (DIBCO) and handwritten document image binarization competition (H-DIBCO) benchmark datasets. Results show that our proposed DP-LinkNet outperforms other state-of-the-art techniques by a large margin. Our implementation and the pre-trained models are available at https://github.com/beargolden/DP-LinkNet.

• Journal of Broadcast Engineering
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• v.26 no.7
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• pp.868-876
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• 2021

Deploying deep neural network model training performs remarkable performance in the fields of Object detection and Instance segmentation. To train these models, features are first extracted from the input image using a backbone network. The extracted features can be reused by various tasks. Research has been actively conducted to serve various tasks by using these learned features. In this process, standardization discussions about encoding, decoding, and transmission methods are proceeding actively. In this scenario, it is necessary to analyze the response characteristics of features against various distortions that may occur in the data transmission or data compression process. In this paper, experiment was conducted to inject various distortions into the feature in the object recognition task. And analyze the mAP (mean Average Precision) metric between the predicted value output from the neural network and the target value as the intensity of various distortions was increased. Experiments have shown that features are more robust to distortion than images. And this points out that using the feature as transmission means can prevent the loss of information against the various distortions during data transmission and compression process.

• Asia Marketing Journal
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• v.16 no.1
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• pp.149-168
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• 2014

This study investigates the effect of perceived risk on attitude toward mobile Social Network Services (SNSs). First, we understand that perceived risk of SNSs is a multidimensional concept, and we study the relationship between attitude and perceived risk such as social risk, performance risk, and privacy risk in SNS environments. Subsequently, the relationships between these multidimensional concepts of perceived risk and attitude are investigated. The result indicates that social, performance, and privacy risk have negative effects on attitude. In addition, the moderated effect of individual characteristic variables such as hedonic value and self-construal are confirmed as mitigating factors that alleviate the negative impact of perceived risk. The Findings show that customers who perceive SNSs to be risky are more likely to have a negative attitude toward SNSs. However, the negative impact of perceived risk on their attitude toward SNSs is alleviated in customers with high hedonic value. Similarly, the negative impact of perceived risk on their attitude toward SNS is weaker with customers in interdependent self-construal. This paper presents effective segmentation variables, such as consumer's motivation (hedonic value) and psychological variable (self-construal), which mitigate the risk perception of customers. Therefore, it provides practical guidelines for the marketing managers in terms of who to target and what kind of strategies to implement in terms of these segmentation variables to approach consumers more efficiently.

• Archives of design research
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• v.19 no.5 s.67
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• pp.243-254
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• 2006

Maniac consumers have a ripple effect on marketing because they are the main body of trends and consumer economy. So It is very important that we should first read needs and wants - in other words, psychological motives. And then we should find maniac consumer segments. This is an exploratory study that was done to obtain an insight for the new maniac consumer market segmentation. It examined the definition and characteristics of digital maniacs in Korea, and it carried out a literature study on consumers who have a similar consumption trend as the maniac users as a pre-study. Also, it looked into the trends and values of the maniac community in Korea, using the previous study's scale for innovative consumers. Next, the study interviewed maniac users using the first data and focused on discovering and grouping the new maniac segments based on the results. The study analyzed the purchase behaviors, decision-making, attitude for involvement and potential needs of the digital maniacs in Korea, and it discovered the segments for the segmentation of maniacs so it could find out the disposition and status of the digital maniacs. Such approach can be used as a strategical due for maniac target marketing and design(customer-oriented marketing and design) in the future.

• Journal of Korea Multimedia Society
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• v.5 no.5
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• pp.571-581
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• 2002

Many periodic broadcasting schemes for near VoD systems are proposed. Recently non-uniform segmentation schemes have been used to develop periodic broadcasting techniques for near VoD. These techniques give significant reductions in start-up latency as compared with more conventional uniform segmentation. However, all of these schemes assume that the videos are CBR-encoded. Since a CBR-encoded video has a target average tate than an VBR encoding, there is potential to obtain further Performance Improvements by using VBR videos. Unfortunately, however, the studies concerning broadcasting with VBR video ate rare and the existing techniques have the problem of virtual loss. In this paper, we modify Skyscraper Broadcasting Scheme for broadcasting with VBR videos which is a representative non-uniform segmentation scheme lot CBR videos. A VBR video can be transmitted at constant bit rate (CBR) by using prefetching. With this idea we propose Modified Skyscraper Broadcasting Schemes for VBR videos and make performance evaluation by simulation. We show that our schemes have a better performance than Skyscraper Broadcasting Scheme for CBR videos.

• Korean Journal of Community Nutrition
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• v.8 no.4
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• pp.556-565
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• 2003

Market segmentation helps providers to find better marketing opportunities and allows foodservice managers to develop the right product for each target market. Therefore, this study, taking university faculty and staff as subject, is intended to diagnose the relative value of service quality attribute, on the basis service quality scenario of faculty foodservice; to suggest price for improving customer loyalty in market segments. A questionnaire was developed ar d mailed to 600 Yonsei university faculty and staffs. A total of 385 questionnaires were usable; resulting in a 58.7％ of faculty and a 69.7％ of staff response rate, respectively. Statistical data analysis was completed using the SAS/Win 6.12 for descriptive Analysis, ANOVA, principal factor analysis, cluster analysis, reliability test and discriminant analysis. The results of the study are as below. Eighteen questions were selected for measuring respondents' lifestyle by AIO method and the seven lifestyle factors derived from factor analysis and aggregated distinct 4 clusters. Service quality attributes of the scenario were determined with 'food quality', 'menu variety', 'atmosphere', 'fast service', and 'clean and sanitation'. 'Food quality', 'menu variety', 'atmosphere', 'fast service', and 'clean and sanitation', in decreasing order, were identified as improving customer loyalty. However, most faculty and staffs were satisfied with the present meal price. The result of this study indicates that the relative value of service quality was differed significantly among the various market segments. 'Food quality', 'menu variety', and 'atmosphere' were determined as major service quality attributes. Thus, customer loyalty could be increased by improving food taste and quality, atmosphere, and service delivery. (Korean J Community Nutrition 8(4) : 556 ∼565, 2003)