• The Journal of Information Systems
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• v.28 no.2
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• pp.73-92
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• 2019

Purpose This study conducted an empirical study on the influence of institutional mechanisms on the formation of customer trust among leading online businesses. This study focused on the construct of PEEIM(Perceived Effectiveness of e-Commerce Institutional Mechanisms) which is the perceived recognition of institutional mechanisms for e-Commerce in general and the construct of PEIS which is the perceived recognition of institutional mechanisms that are implemented by vendors. Design/methodology/approach The online and offline surveys were conducted for the leading online shopping vendors in Korea and 292 data were used for the empirical analysis. The research model was tested using partial least squares structural equation modeling (PLS-SEM) in this study. The full measurement model including the formative second-order constructs was examined with the exploratory factor analysis. The structural model was analyzed via a two-stage approach. To analyze the research model this study used Smart PLS 2.0 program. Findings The findings showed that PEEIM negatively moderates the relationship between satisfaction in vender and trust in vender, but had no moderating effect between trust in vender and repurchase intention. In addition, the institutional mechanisms of vendors(PEIS) have been shown to have a direct impact on the vender's trust.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.111-122
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• 2021

Building footprint extraction is an active topic in the domain of remote sensing, since buildings are a fundamental unit of urban areas. Deep convolutional neural networks successfully perform footprint extraction from optical satellite images. However, semantic segmentation produces coarse results in the output, such as blurred and rounded boundaries, which are caused by the use of convolutional layers with large receptive fields and pooling layers. The objective of this study is to generate visually enhanced building objects by directly extracting the vertices of individual buildings by combining instance segmentation and keypoint detection. The target keypoints in building extraction are defined as points of interest based on the local image gradient direction, that is, the vertices of a building polygon. The proposed framework follows a two-stage, top-down approach that is divided into object detection and keypoint estimation. Keypoints between instances are distinguished by merging the rough segmentation masks and the local features of regions of interest. A building polygon is created by grouping the predicted keypoints through a simple geometric method. Our model achieved an F1-score of 0.650 with an mIoU of 62.6 for building footprint extraction using the OpenCitesAI dataset. The results demonstrated that the proposed framework using keypoint estimation exhibited better segmentation performance when compared with Mask R-CNN in terms of both qualitative and quantitative results.

• Archives of Plastic Surgery
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• v.49 no.6
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• pp.782-784
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• 2022

Diabetic foot ulcers are a severe complication of diabetes, and their management requires a multidisciplinary approach for optimal management. When treating these ulcers, limb salvage remains the ultimate goal. In this article, we present the "hanging" free flap for the reconstruction of chronic lower extremity diabetic ulcers. This two-staged approach involves standard free flap harvest and inset; however, following inset the "hanging" pedicle is covered within a skin graft instead of making extraneous incisions within the undisturbed soft tissues or tunnels that can compress the vessels. After incorporation, a second-stage surgery is performed in 4 to 6 weeks which entails pedicle division, flap inset revision, and end-to-end reconstruction of the recipient vessel. Besides decreasing the number of incisions on diabetic patients, our novel technique utilizing the "hanging" pedicle simplifies flap monitoring and inset and allows reconstruction of recipient vessels to reestablish distal blood flow.

• Proceedings of the Korea Information Processing Society Conference
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• 2007.11a
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• pp.34-37
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• 2007

Face recognition is still a challenging problem in pattern recognition field which is affected by different factors such as facial expression, illumination, pose etc. The facial feature such as eyes, nose, and mouth constitute a complete face. Mouth feature of face is under the undesirable effect of facial expression as many factors contribute the low performance. We proposed a new approach for face recognition under facial expression applying two cascaded classifiers to improve recognition rate. All facial expression images are treated by general purpose classifier at first stage. All rejected images (applying threshold) are used for adaptation using GA for improvement in recognition rate. We apply Gabor Wavelet as a general classifier and Gabor wavelet with Genetic Algorithm for adaptation under expression variance to solve this issue. We have designed, implemented and demonstrated our proposed approach addressing this issue. FERET face image dataset have been chosen for training and testing and we have achieved a very good success.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1604-1618
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• 1995

In the process of mechanical assembly design, assembly modeling systems have been used mainly for the design verification before manufacturing by enabling to check the interference and/ or the dynamic and kinematic performance. However, the conventional assembly modeling systems have a shortcoming that they can not be used in the initial design stage but can be used only after the design is fully completed. In other words conventional assembly modeling systems provide bottom-up modeling which means that the detailed modeling of components must precede the definition of relationships between them. To resolve this problem, an assembly modeling system is proposed to provide a top-down modeling environment in which components and assembly can be modeled simultaneously. To this end, an assembly data structure suitable for top-down assembly modeling has been established. Feature positioning Module(FPM) using geometric constraints has been also developed. The Sekective Solving Method proposed for FPM is based on the priority between the constraint equations and enables the designer's intent expressed by geometric constraints to be maintained throughout the whole modeling process. Finally, the feature based modeling technique using two-level features has been developed. Two-level features include an abstract model and a detailed model in a merged form in non-manifold data frame.

• Archives of Plastic Surgery
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• v.37 no.6
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• pp.775-778
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• 2010

Purpose: Reconstruction of soft tissue defects with osteomyelitis in the lower third of the leg represents a challenge to plastic surgeons. Moreover, it is more arduous in multimorbid patients. One excellent option for reconstruction of these defects is to use a delayed distally based sural flap. Methods: We successfully used delayed distally based sural flap with a two-step procedure. During the first operation, radical debridement and elevation of flap were performed. The raised flap was fixed again at the donor site. The delay period ranged from seven to ten days. Between August 2008 and July 2009, we underwent operations for five patients using this technique. The size of flap varied from $10{\times}6\;cm$ to $12{\times}14\;cm$. Results: All flaps successfully survived. Partial skin loss of the grafted site was seen in two patients but no further surgical procedure was required for wound healing. Complaints of hypoesthesia on the lateral part of the foot was observed. In a three month follow-up period, hypoesthesia was resolved spontaneously. Conclusion: Delayed procedure improves the viability of distally based sural flap in high risk, critically multimorbid patients. We recommend that, if a two-stage operative approach is required, the delayed procedure should be considered.

• The KIPS Transactions:PartB
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• v.15B no.5
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• pp.477-486
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• 2008

Facial expression, which changes face geometry, usually has an adverse effect on the performance of a face recognition system. To improve the face recognition rate, we propose a normalization method of facial expression to diminish the difference of facial expression between probe and gallery faces. Two approaches are used to facial expression modeling and normalization from single still images using a generic facial muscle model without the need of large image databases. The first approach estimates the geometry parameters of linear muscle models to obtain a biologically inspired model of the facial expression which may be changed intuitively afterwards. The second approach uses RBF(Radial Basis Function) based interpolation and warping to normalize the facial muscle model as unexpressed face according to the given expression. As a preprocessing stage for face recognition, these approach could achieve significantly higher recognition rates than in the un-normalized case based on the eigenface approach, local binary patterns and a grey-scale correlation measure.

• Radiation Oncology Journal
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• v.9 no.2
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• pp.351-359
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• 1991

The current LINAC technique for radiosurgery utilizes a single isocenter approach with multiple noncoplanar arcs. This approach results in spherical dose distributions in the target. Many arteriovenous malformations and tumors suitable for radiosurgical treatment have non-spherical or irregular shapes. The basic approach presented in this paper is to use two or multiple isocenters with standard arcs to shape irregular target volumes through the use of multiple spherical targets. Selection of reasonable irradiation parameters in the first stage is critical to the success of real-time optimization. A useful guideline for optimum isocenter separation and collimator size is developed to shape the target margin uniformly with an desired isodose surface for an elongated target. The implementation of multiple isocenters with three dimensional dose model and application of multiple isocenters approach to several cases are discussed.

• Journal of the Korean Chemical Society
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• v.68 no.4
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• pp.221-234
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• 2024

The purpose of this study was to examine the impact of Argument-based Inquiry approach on elementary school students' critical thinking in elementary school science class. For this purpose, 23 students from two 5th grade elementary school classes in a metropolitan city were selected. One class (11 students) was assigned as the experimental group which Argument-based inquiry approach on 10 topics were applied. To determine the impact of Argument-based Inquiry approach on critical thinking, we analyzed the results of critical thinking tests before and after class and recordings of the discussion process of students in the experimental group. As a result of the critical thinking analysis, the average score of the experimental group in the deduction section was statistically and significantly higher than that of the comparative group. And as a result of analysis of recordings of the discussion process, students used deductive reasoning more often than inductive reasoning, and their use of this reasoning increased significantly at the claim·evidence stage.

• Korean Journal of Construction Engineering and Management
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• v.10 no.4
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• pp.87-100
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• 2009

The quality of early cost estimates is critical to the feasibility analysis and budget allocation decisions for public capital projects. Various researches have been attempted to develop cost prediction models in the early stage of a construction project. However, existing studies are limited on its applicability to actual projects because they focus primarily on a specific phase as well as utilize restricted information while the amount of information collectable differs from one another along with the project stages. This research aims to develop two-staged cost estimation model for the schematic planning and preliminary design process of a construction projects, considering the available information of each phase. In the schematic planning stage where outlined information of a project is only available, the Case-Based Reasoning model is used for easy and rapid elicitation of a project cost based on the extensive database of more than 90 actual highway construction projects. Then, the representing quantity-based model is proposed for the preliminary design stage where more information on the quantities and unit costs are collectable based on the alternative routes and cross-sections of a highway project. Real case studies are used to demonstrate and validate the benefits of the proposed approach. Through the two-stage cost estimation system, users are able to hold a timely prospect to presume the final cost within the budge such that feasibility study as well as budget allocation decisions are made on effectively and competitively.