• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.131-142
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• 2018

In Korea, for the past 50 years, industrial parks have played an important role in economic growth as a cluster of national key industries. However, due to various problems of these old industrial parks, they are weakening competitiveness. It is necessary to be converted into a model for the management and fostering of high-tech industrial complex park by classifying them into development plans, management plans, and support plans according to types and characteristics of industrial parks. For this purpose, we propose CIPs (Connected-Industrial parks) using new technologies such as Cloud Computing, RFID, WSN, CPS, and Big Data analysis based on IoT. It is a hub that supports various services in transportation, warehousing and manufacturing fields while possessing and operating physical assets as concept. each CIP (Connected-Industrial park) is connected and expanded Through such CIPs, network-type collaborative manufacturing and intelligent logistics innovation enables cost reduction, delivery shortening, quality improvement.

• Korean Journal of Computational Design and Engineering
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• v.10 no.6
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• pp.444-454
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• 2005

Recently, the requirements of multi-resolution models of a solid model, which represent an object at multiple levels of feature detail, are increasing for engineering tasks such as analysis, network-based collaborative design, and virtual prototyping and manufacturing. The research on this area has focused on several topics: topological frameworks for representing multi-resolution solid models, criteria for the level of detail (LOD), and generation of valid models after rearrangement of features. As a solution to the feature rearrangement problem, the new concept of the effective zone of a feature is introduced in the former part of the paper. In this paper, we propose a feature-based non-manifold modeling system to provide multi-resolution models of a feature-based solid or non-manifold model on the basis of the effective feature zones. To facilitate the implementation, we introduce the class of the multi-resolution feature whose attributes contain all necessary information to build a multi-resolution solid model and extract LOD models from it. In addition, two methods are introduced to accelerate the extraction of LOD models from the multi-resolution modeling database: the one is using an NMT model, known as a merged set, to represent multi-resolution models, and the other is storing differences between adjacent LOD models to accelerate the transition to the other LOD. We also suggest the volume of the feature, regardless of feature type, as a criterion for the LOD. This criterion can be used in a wide range of applications, since there is no distinction between additive and subtractive features unlike the previous method.

• Journal of Ocean Engineering and Technology
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• v.26 no.2
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• pp.58-67
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• 2012

Recently, both the integration of product data during design and production and the effective management of information during full lifecycles have attracted attention from shipyards and ship owners as a result of recycling regulations and a desire for efficient operations. Generally, PLM (Product Lifecycle Management) supports a collaborative environment during the BOL (Beginning of Life) stage, while an ALM (Asset Lifecycle Management) system provides all of the information required to maintain, overhaul, and discard/recycle all or part of a vessel during the MOL (Middle of Life) and EOL (End of Life) stages. The main goal of this paper is to suggest the fundamental configuration of a PALM (Product Asset Lifecylce Management) system and a method that can be used to utilize a marine vessel's lifecycle information during the MOL, emphasizing the maintenance information during the middle of life. The authors also suggest a PALM system configuration in which lifecycle information can be collected by a PEID (Product Embedded Information Device) integrating a microcomputer, sensors, and wireless network communication. Through a prototype PALM system, the suggested features and PALM system configuration are implemented.

• The KIPS Transactions:PartA
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• v.9A no.1
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• pp.29-36
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• 2002

For the efficient collaboration awareness, the CSCW (Computer-Supported Cooperative Work) systems provide functions such as telepointing, snap-shot, and document/project tracking. Among these, telepointing allows an event occurrence on the shared window of a local computing system to be presented in remote computing systems. Although telepointing has been mentioned in the literature, few research papers deal with the functional requirements and protocols for telepointing. This parer describes the functional requirements and payload format for RTP (Real-Time Transport Protocol)-based telepointing. In order to evaluate the performance of the proposed RTP-barred telepointing, we have implemented a whiteboard and compared it with that of the Microsoft Netmeeting. The evaluation results show that the proposed telepointing performs better in terms of CPU usage and the amount of network traffic.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1047-1053
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• 2007

As the acceleration of digital convergence has been deepen and extended to convergence of human, things, and space, the various forms of convergence have been appeared and extended. This paper presents the aim of the system's change which embodies the collaborative electronic government of the application service, which applies the UIT as the changed feature from e-Gov to u-Gov and attains the administrative idea which the u-Gov pursues. It analyzes and applies the propulsive plan of the policies to u-Gov, which is resulted from the variation of the convergence community, and the feature of the UIT, and then it proposed the service model of the new u-Gov with circulation instance adumbration which applies the UIT as the objective realization means of the ultimate administration.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.171-182
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• 2019

As online shopping malls continue to grow in popularity, various chances of consumption are provided to customers. Customers decide the purchase by exploiting information provided by shopping malls such as the reviews of actual purchasing users, the detailed information of items, and so on. It is required to provide objective and reliable information because customers have to decide on their own whether the massive information is credible. In this paper, we propose a personalized recommendation method considering an item confidence to recommend reliable items. The proposed method determines user preferences based on various behaviors for personalized recommendation. We also propose an user preference measurement that considers time weights to apply the latest propensity to consume. Finally, we predict the preference score of items that have not been used or purchased before, and we recommend items that have highest scores in terms of both the predicted preference score and the item confidence score.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.1
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• pp.165-181
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• 2022

The fashion industry is creating innovative business models using artificial intelligence. To efficiently utilize artificial intelligence (AI), fashion data must be classified. Until now, such data have been classified focusing only on the objective properties of fashion products. Their subjective attributes, such as fashion brand sensibilities, are holistic and heuristic intuitions created by a combination of design elements. This study aims to improve the performance of collaborative filtering in the fashion industry by extracting fashion brand sensibility using computer vision technology. The image data set of fashion brand sensibility consists of high-end fashion brand photos that share sensibilities and communicate well in fashion. About 26,000 fashion photos of 11 high-end fashion brand sensibility labels have been collected from the 16FW to 21SS runway and 50 years of US Vogue magazines beginning from 1971. We use EfficientNet-B1 to establish the main architecture and fine-tune the network with ImageNet-ILSVRC. After training fashion brand sensibilities through deep learning, the proposed model achieved an F-1 score of 74% on accuracy tests. Furthermore, as a result of comparing AI machine and human experts, the proposed model is expected to be expanded to mass fashion brands.

• Journal of Preventive Medicine and Public Health
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• v.56 no.4
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• pp.291-302
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• 2023

Objectives: Disability weights require regular updates, as they are influenced by both diseases and societal perceptions. Consequently, it is necessary to develop an up-to-date list of the causes of diseases and establish a survey panel for estimating disability weights. Accordingly, this study was conducted to calculate, assess, modify, and validate disability weights suitable for Korea, accounting for its cultural and social characteristics. Methods: The 380 causes of disease used in the survey were derived from the 2019 Global Burden of Disease Collaborative Network and from 2019 and 2020 Korean studies on disability weights for causes of disease. Disability weights were reanalyzed by integrating the findings of an earlier survey on disability weights in Korea with those of the additional survey conducted in this study. The responses were transformed into paired comparisons and analyzed using probit regression analysis. Coefficients for the causes of disease were converted into predicted probabilities, and disability weights in 2 models (model 1 and 2) were rescaled using a normal distribution and the natural logarithm, respectively. Results: The mean values for the 380 causes of disease in models 1 and 2 were 0.488 and 0.369, respectively. Both models exhibited the same order of disability weights. The disability weights for the 300 causes of disease present in both the current and 2019 studies demonstrated a Pearson correlation coefficient of 0.994 (p=0.001 for both models). This study presents a detailed add-on approach for calculating disability weights. Conclusions: This method can be employed in other countries to obtain timely disability weight estimations.

• The Journal of the Convergence on Culture Technology
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• v.9 no.5
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• pp.951-956
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• 2023

In the current situation where systematic and active disaster management is becoming more important, domestic libraries do not have their own disaster management plans or support systems. In order to improve these problems, this study looked at overseas cases. Among them, we looked at Japan, where related cases and research are actively underway due to its exposure to various geopolitical disasters. In particular, we focused on cases of public-private cooperation established after the Great East Japan Earthquake. Association's Library Disaster Response Committee and saveMALK, a voluntary network of experts. The Library Disaster Response Committee played a central role in organizing donations and volunteer activities, and saveMALK played a role in collecting and sharing information by forming a collective intelligence among relevant experts. This analysis of the Japanese case has positive implications for building collaborative disaster management system.

• The Journal of Korean Academic Society of Nursing Education
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• v.30 no.2
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• pp.182-191
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• 2024

Purpose: The purpose of this study was to explore the characteristics of social networks among registered nurses in acute nursing care units. Methods: This study used a survey design. Four nursing units from two acute hospitals were selected using a convenience method, and 83 nurses from those nursing units participated in the study in July 2022. The positive influences among nurses included friendship, collaboration, advice, and referent networks, and the negative influences included avoidance and bullying networks. Using the NetMiner program, the k-means clustering technique was applied to create groups of nodes with similar characteristics. The general characteristics of the participants were analyzed by mean, standard deviation, frequency, and ANOVA or chi-squared test. Results: As a result of dividing the 83 nurse participants into four clusters, positive influencers, silent peers, unwelcome peers, and active bullies were identified. Positive influence group nurses were frequently mentioned in the friendship, collaboration, advice, and referent networks. On the other hand, nurses in the unwelcome group and the active bullying group were frequently mentioned in the avoidance and bullying networks. Conclusion: Social networks that have a positive or negative impact on nursing performance are created through different relationships between nurses. Nurse managers can use the findings to create a more supportive and collaborative environment. Further research is needed to develop intervention programs to improve interactions and relationships between fellow nurses.