• Journal of Distribution Science
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• v.13 no.11
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• pp.47-58
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• 2015

Purpose - This study aims to seek determinants of department store sales commission rates under consignment contracts based on transaction cost theory, the power-dependence view, and the resource-based view. A consignment contract is a unique contract where the retailer, over a given period, takes possession of goods owned by a supplier, promotes the sales of these goods, and receives a profit share from their sales. Under this contract, the supplier owns the goods until they are sold. In department stores in South Korea, over 70% of overall sales comes through consignment contracts. In other words, this is the most popular contract agreement between large retailers and vendors in South Korea. Consignment contracts yield high profits to department stores with minimal sales uncertainty, stock cost, and marketing investment. Many suppliers believe the consignment contract commission rates are too high. However, department stores disagree. They state that the commissions are not high as they generate new value for the suppliers by accumulating up-to-date merchandise and supporting various marketing programs on their behalf. Recently, consignment contracts have been critically examined and scrutinized by politicians, mass media, and the public of Korea. This study further intends to derive implications reflecting both buyer and seller perspectives as well as offer insights to policy makers in making appropriate decisions. Research design, data, and methodology - To verify the proposed research model and test hypotheses, the authors selected 164 suppliers, which currently have relationships with department stores. This study carefully investigated the reliability, content validity, convergent validity, and discriminant validity of the proposed model. The data were analyzed using SPSS 18.0 and AMOS structural equation modeling program Results - For the transaction cost theory and the power-dependence view, the results indicated that product diversity and demand volatility had a positive impact on the sales dependence on a department store. Dependence in turn had a positive effect on the sales commission under the consignment contract. Based on the resource-based view, the department store's marketing capability, the supplier's perception toward merchandising, and supporting activities could enhance the department store's channel leadership in the buyer-seller relationship. Subsequently, the channel leadership had a positive effect on the sales commission. However, product complexity had no relationship with department store dependence. Conclusions - This is the first empirical research that investigates the determinants of sales commissions under consignment contracts in the domestic retail industry. This study reveals several theoretical and practical implications for both marketing scholars and marketers. In terms of theoretical implication, this study integrated and enlarged certain theoretical background, such as transaction cost theory, the power-dependence view, and the resource-based view, to explain the determinants of sales commissions under consignment contracts that include sales revenue. From a business management viewpoint, this research offers useful insights for policy makers by applying two different perspectives, both the manufacturer and the retailer, in terms of the sales commission issue under a consignment contract.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.1 s.343
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• pp.27-36
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• 2006

Conventional delay-insensitive (DI) data encodings usually require 2N+1 wires for transferring N-bit. To reduce complexity and power dissipation of wires in designing a large scaled chip, an encoder and a decoder circuits, where N-bit data transfer can be peformed with only N+l wires, are proposed. These circuits are based on a quasi delay-insensitive (QDI) model and designed by using current-mode multiple valued logic (CMMVL). The effectiveness of the proposed data transfer mechanism is validated by comparisons with conventional data transfer mechanisms using dual-rail and 1-of-4 encodings through simulation at the 0.25 um CMOS technology. In general, simulation results with wire lengths of 4 mm or larger show that the CMMVL scheme significantly reduces delay-power product ($D{\ast}P$) values of the dual-rail encoding with data rate of 5 MHz or more and the 1-of-4 encoding with data rate of 18 MHz or more. In addition, simulation results using the buffer-inserted dual-rail and 1-of-4 encodings for high performance with the wire length of 10 mm and 32-bit data demonstrate that the proposed CMMVL scheme reduces the D*P values of the dual-rail encoding with data rate of 4 MHz or more and 1-of-4 encoding with data rate of 25 MHz or more by up to $57.7\%\;and\;17.9\%,$ respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.1
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• pp.26-39
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• 2007

In recent years, rate control is an important technique in real time video communication applications using H.264/AVC. Many existing rate control algorithms employ the quadratic rate-distortion model, which is determine the target bits for each P frame. In this paper, a new rate control algorithm for transmission of H.264/AVC video bit stream through CBR(Constant Bit Rate) channel is proposed. The proposed algorithm predicts an adaptive QP(Quantization Parameter) for improving video distortion, due to high motion and abruptly scene change, which target bit rate and MAD(Mean of Absolute Difference) for current frame considering image complexity variance between previous and current frames. Additionally, it uses frame skip technique to maintain bit stream within a manageable range and protect buffer from overflow or underflow. Experimental results show that the proposed method gives a quality improvement of about 0.5dB when compared to previous rate control algorithm. Also our proposed algorithm encodes the video sequences with less frame skipping compared to the existing rate control for H.264/AVC.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.12
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• pp.73-82
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• 2008

There are several approaches for reducing the ROB(Reorder Buffer) complexity in processors. The one technique that makes the simplest ROB ports relies on a distributed implementation that spreads the centralized ROB structure across the functional units(FUs). Each distributed buffers are decided on the size of them by workload of the functional units. The performance of the processor depends on the size of distributed ROB. However, most of previous works have depended on the simulation results to decide the optimsize of distributed ROB. In this Paper, we use an analytical model based on the M/M/1 Queuing theory to determine the optimum size of each distributed ROB. Our schemes are evaluated by using the simulation performed by the CPU2000 benchmarks. We are able to choose the optimum size of distributed ROB showing the 99.2% performance compared with existing superscalar processors. We can save 82% hardware resources in ports and reduce more than 30% of delay when ROB and distributed ROB proposed in this paper are designed by HDL.

• Information Systems Review
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• v.16 no.3
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• pp.135-160
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• 2014

Most Social Network Service (SNS) provide online chat, video and file sharing, blogging and others. Because of this advantage, people depend on SNS to communicate with others. However, recently SNS encourage people to reveal too much information broadly so SNS users are concerned about privacy invasion and data spill. They also feel fatigue in process of touching people they don't know while using SNSs. That is the reason why they attempt to switch from opened SNS to Closed SNS. Therefore, the purpose of this study is to empirically investigate and analyze the effect of the factors on the SNS users' switching behavior when using SNS. To accomplish this purpose, this research adopted "Push-Pull-Mooring (PPM)" framework. The PPM is proposed by population geologist, who used it to explain the incentives of demographic migration. Following PPM model, this research empirically examines the three categories of antecedents for SNS switching intention toward closed SNS: push (i.e., weak connection, privacy concern, relative complexity), pull (i.e., enjoyment, belongingness, peer influence), mooring (i.e., SNS fatigue, user resistance) factors. The survey was conducted for 285 users on SNS communities in Korea. The results of this study are as follows; First, wear connection and privacy concern are significantly related to SNS switching intention. Second, enjoyment and belongingness are significantly related to SNS switching intention. Finally, the results show that SNS fatigue has a moderating effect on the links between push factors and SNS switching Intention. Also, user resistance has a moderating effect on the links between pull factors and SNS switching Intention. These findings contribute to the SNS literature both theoretically and practically.

• Land and Housing Review
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• v.2 no.3
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• pp.249-258
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• 2011

In order to achieve an efficient urban regeneration of the nation, it is required to determine the extent of decline nation-wide and the declined areas for each district and also to evaluate the potentials of the concerned areas. For this task to be accomplished, a construction of a comprehensive diagnostic system based on spatial information considering diversity and complexity is required. In this study, a total information system architecture for urban regeneration is designed as part of the construction of such a diagnostic system. In order to develop the system, a city and district level unit decline diagnostic indicators has been constructed and a decline diagnostic system has been developed. Also, a scheme to promote the advancement of the system is proposed. The DB construction is based on the city and district level nation-wide and metadata for the concerned level is constructed as well. The system is based on the Open API and designed to be flexible for extension. Also, an RIA-based intuitive UI has been implemented. Main features of the system consist of the management of the indicators, diagnostic analysis (city and district level decline diagnosis), related information, etc. As for methods for the advancement, an information model in consideration of the spation relations of the urban regeneration DB has been designed and application methods of semantic webs. Also, for improvement methods for district unit analytical model, district level analysis models, GIS based spatial analysis platforms and linked utiliation of KOPSS analysis modules are suggested. A use of a total information system for urban regeneration is anticipated to facilitate concerned policy making through the identification of the status of city declines to identify and the understanding of the demands for regeneration.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.273-282
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• 2005

Real-time Object tracking is an important field in developing vision applications such as surveillance systems and vision based navigation. mean-shift algerian and Condensation algorithm are widely used in robust object tracking systems. Since the mean-shift algorithm is easy to implement and is effective in object tracking computation, it is widely used, especially in real-time tracking systems. One of the drawbacks is that it always converges to a local maximum which may not be a global maximum. Therefore, in a cluttered environment, the Mean-shift algorithm does not perform well. On the other hand, since it uses multiple hypotheses, the Condensation algorithm is useful in tracking in a cluttered background. Since it requires a complex object model and many hypotheses, it contains a high computational complexity. Therefore, it is not easy to apply a Condensation algorithm in real-time systems. In this paper, by combining the merits of the Condensation algorithm and the mean-shift algorithm we propose a new model which is suitable for real-time tracking. Although it uses only a few hypotheses, the proposed method use a high-likelihood hypotheses using mean-shift algorithm. As a result, we can obtain a better result than either the result produced by the Condensation algorithm or the result produced by the mean-shift algorithm.

• Journal of Distribution Research
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• v.17 no.3
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• pp.93-113
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• 2012

Early conflict research in channel and organization area have focused on the definition of conflict construct, its cause, consequence and identified conflict resolution management. Recent studies about conflict, however, have explored new assumption of complexity, a multidimensional conflict construct, contextual conflict management strategies, positive and negative conflict/consequence, and the conflict resolution strategy. Although many literatures exists on channel conflict resolution, little research has been done about relationship learning and performance from conflict resolution perspective. This study explores how channel members can achieve a relationship learning, as a conflict resolution mechanism, which enhance co-created value in marketing channel relationship. Therefore we propose that conflict resolution strategies(collaborating behavior and avoiding behavior) influence channel performance(effectiveness and efficiency) through relationship learning processes(learning via information exchange, joint interpretation and coordination, relationship-specific knowledge memory), in view of buyer-seller relationship. The research model is shown at

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.959-971
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• 2019

CNN (Convolutional Neural Network) is one representative deep learning algorithm, which can extract high-level spatial and spectral features, and has been applied for hyperspectral image classification. However, one significant drawback behind the application of CNNs in hyperspectral images is the high dimensionality of the data, which increases the training time and processing complexity. To address this problem, several CNN based hyperspectral image classification studies have exploited PCA (Principal Component Analysis) for dimensionality reduction. One limitation to this is that the spectral information of the original image can be lost through PCA. Although it is clear that the use of PCA affects the accuracy and the CNN training time, the impact of PCA for CNN based hyperspectral image classification has been understudied. The purpose of this study is to analyze the quantitative effect of PCA in CNN for hyperspectral image classification. The hyperspectral images were first transformed through PCA and applied into the CNN model by varying the size of the reduced dimensionality. In addition, 2D-CNN and 3D-CNN frameworks were applied to analyze the sensitivity of the PCA with respect to the convolution kernel in the model. Experimental results were evaluated based on classification accuracy, learning time, variance ratio, and training process. The size of the reduced dimensionality was the most efficient when the explained variance ratio recorded 99.7%~99.8%. Since the 3D kernel had higher classification accuracy in the original-CNN than the PCA-CNN in comparison to the 2D-CNN, the results revealed that the dimensionality reduction was relatively less effective in 3D kernel.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.21-35
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• 2009

KOMPSAT-2 is the seventh high-resolution image satellite in the world that provides both 1m-grade panchromatic images of the GSD and 4m-grade multispectral images of the GSD. It's anticipated to be used across many different areas including mapping, territory monitoring and environmental watch. However, due to the complexity and security concern involved with the use of the MSC, the use of KOMPSAT-2 images are limited in terms of geometric images, such as satellite orbits and detailed mapping information. Therefore, this study aims to produce DEM and orthoimage by using the stereo images of KOMPSAT-2, and to explore the applicability of geo-spatial information with KOMPSAT -2. Orientation interpretations were essential for the production of DEM and orthoimage using KOMPSAT-2 images. In the study, they are performed by utilizing both RPC and GCP. In this study, the orientation interpretations are followed by the generation of DEM and orthoimage, and the analysis of their accuracy based on a 1:5,000 digital map. The accuracy analysis of DEM is performed and the results indicate that their altitudes are, in general, higher than those obtained from the digital map. The altitude discrepancies on plains, hills and mountains are calculated as 1.8m, 7.2m, and 11.9m, respectively. In this study, the mean differences between horizontal position between the orthoimage data and the digital map data are found to be ${\pm}3.081m$, which is in the range of ${\pm}3.5m$, within the permitted limit of a 1:5,000 digital map. KOMPSAT-2 images are used to produce DEM and orthoimage in this research. The results suggest that DEM can be adequately used to produce digital maps under 1:5,000 scale.