• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.25-34
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• 2006

In this paper DynaMoNET is suggested as a novel IPv6-based multi-homed mobile network architecture which is composed of nested mobile ad hoc networks dynamically coming together through wireless personal area networks. Each ad hoc network has a mobile router which may work as a root mobile router instead of fixed mobile routers in a DynaMoNET. A root mobile router provides the reliable Internet connectivity for the entire mobile network. This paper includes a innovative handover protocol for multi-homed mobile networks, network switchover algorithm considering multiple decision factors, root mobile router election process based on token-based algorithm fast root mobile router discovery algorithm and fault avoidance mechanism to support reliable Internet connectivity. Finally the system architecture of a mobile router is given in detail.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.1-17
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• 2007

A virtual enterprise (VE) can be mapped into a multi-agent system (MAS) that consists of various agents with specific role(s), communicating with each other to accomplish common goal(s). However, a MAS for enacting VE requires more advanced mechanism such as context that can guarantee autonomy and dynamism of VE members considering heterogeneity and complex structure of them. This paper is to suggest a context-based MAS as a platform for constructing and managing virtual enterprises. In the Context-based MAS a VE is a collection of Actor, Interaction (among Actors), Actor Context, and Interaction Context. It can raise the speed and correctness of decision-making and operation of VE enactment using context, i.e., information about the situation (e.g., goal, role, task, time, location, media) of Actors and Interactions, as well as simple data of their properties. The Context-based MAS for VE we proposed('VECoM') may consists of Context Ontology, Context Model, Context Analyzer, and Context Reasoner. The suggested approach and system is validated through an example where a VE tries to find a partner that could join co-development of new technology.

• Clinics in Shoulder and Elbow
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• v.18 no.2
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• pp.86-90
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• 2015

Background: Although there are several methods for evaluating bone quality, Hounsfield units (HU), a standardized computed tomography (CT) attenuation coefficient, provide a useful tool for estimating focal bone mineral density (BMD). The aim of this study is to investigate the HU for evaluating the degree of osteoporosis in greater tuberosity with regard to anchor positioning. Methods: Forty patients diagnosed as normal on shoulder CT were included and categorized according to age and gender. Axially sectioned CT images were processed to 3-dimensional models containing information about bone quality using Mimics (14.11 platform v14.1.1.1 Materialise). Three-dimensional anchors were simulated and positioned according to 6 regions of interest (ROI) in the greater tuberosity classified using Tingart's system. Mean HU of intra-anchor volumes in the 6 regions was measured. Results: A significant decrease in HU was observed with increasing age (p=0.0001) and menopause (p<0.001). A significant difference in HU was found between male and female groups with males showing the higher values (p=0.0001). HU of proximal areas of ROI was higher than those of distal areas (p<0.005). However, although mean HU of distal posterior ROI showed the lowest values, no statistically significant difference was found between anterior, middle, and posterior regions (p=0.087). Conclusions: Mean HU of ROIs provides a tool for preoperative assessment of focal BMD, which is a factor of suture anchor stability and can be used to aid decision-making regarding secure anchor positioning for rotator cuff repair. Our data support that the most secure point is the proximal regions of ROI.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.311-318
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• 2013

Recently, there have been many studies on RFID-based SCM. Yet, studies of synchronizing errors caused by tracking logistics information in supply chain, and activating & monitoring RFID infra is still insufficient. Also, there is no case of developing the intelligent SCM system enabling total monitoring and controlling RFID Infra by applying these technologies. Logistics information synchronization based Smart SCM model is intelligent supply chain service model to monitor the status of the RFID equipments in supply chain and the synchronization of the logistics process in each logistics point through one integrated view, as well as to react instantly by providing the information to help the various decision makings, when the emergency occurs. By adopting global logistics standard, RFID related standard specification, EPCIS standard, and SSI middleware platform, this model provides the domestic standard specification.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.168-175
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• 2021

In this study, a transdisciplinary convergence education program was developed to enhance the understanding for classification of reptiles and amphibians in biology education and also to increase AI (Artificial Intelligence) capability by using artificial intelligence education. The main content is to solve the classification of reptiles and amphibians that has been dealt with for a long time in biology education, using a decision tree and ML4K (Machine Learnig for Kids), it was designed for a total of 3 lessons. Experts review was conducted on the developed education program, as a result, the I-CVI(Item Content Validity Index) value was .88~1.00 so that can secure content validity. This education program has the advantage of being able to simultaneously learn about the learning contents of artificial intelligence in informatics and the classification of vertebrates in the biological education. In addition, since it is configured to minimize the cognitive load in the AI using part, it is characterized by the fact that all of any teachers can apply it their lesson easily.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.22-32
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• 2019

On offshore platforms, oil and gas leaks are apt to be the initial events of major accidents that may result in significant loss of life and property damage. To prevent accidents induced by leakage, it is vital to perform a case-specific and accurate risk assessment. This paper presents an integrated method of Ddynamic Qquantitative Rrisk Aassessment (DQRA)-using the Decision Making Trial and Evaluation Laboratory (DEMATEL)-Bayesian Network (BN)-for evaluation of the system vulnerabilities and prediction of the occurrence probabilities of accidents induced by leakage. In the method, three-level indicators are established to identify factors, events, and subsystems that may lead to leakage, fire, and explosion. The critical indicators that directly influence the evolution of risk are identified using DEMATEL. Then, a sequential model is developed to describe the escalation of initial events using an Event Tree (ET), which is converted into a BN to calculate the posterior probabilities of indicators. Using the newly introduced accident precursor data, the failure probabilities of safety barriers and basic factors, and the occurrence probabilities of different consequences can be updated using the BN. The proposed method overcomes the limitations of traditional methods that cannot effectively utilize the operational data of platforms. This work shows trends of accident risks over time and provides useful information for risk control of floating marine platforms.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.36-48
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• 2020

App market has continuously been growth since its launch. The market revenues will reach about 1,000 billion US dollars in 2019. App is a core service for smartphone. Currently, there are more than 1.5 million mobile apps in App platform calling out for attention. So, if you are looking at developing a successful app, you need to have a solid marketing and distribution strategy. Online word of mouth(eWOM) is one of the most effective, powerful App marketing method. eWOM affect potential consumers' decision making, and this effect can spread rapidly through online social network. Despite the increasing research on word of mouth, only few studies have focused on content analysis. Most of studies focused on the causes and acceptance of eWOM and eWOM performance measurement. This study aims to content analysis of mobile apps review In 2013, Google researchers announced Word2Vec. This method has overcome the weakness of previous studies. This is faster and more accurate than traditional methods. This study found out the relationship between mobile app reviews and checked for reactions by Word2vec.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.185-192
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• 2022

This study investigates the effect of the semi-supervised learning(SSL) method on predicting default risk of peer-to-peer(P2P) loans. Despite its proven performance, the supervised learning(SL) method requires labeled data, which may require a lot of effort and resources to collect. With the rapid growth of P2P platforms, the number of loans issued annually that have no clear final resolution is continuously increasing leading to abundance in unlabeled data. The research data of P2P loans used in this study were collected on the LendingClub platform. This is why an SSL model is needed to predict the default risk by using not only information from labeled loans(fully paid or defaulted) but also information from unlabeled loans. The results showed that in terms of default risk prediction and despite the use of a small number of labeled data, the SSL method achieved a much better default risk prediction performance than the SL method trained using a much larger set of labeled data.

• Knowledge Management Research
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• v.23 no.1
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• pp.1-26
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• 2022

With the spread of social networks, platform-based social commerce has grown rapidly with the use of multiple smart devices. Given the rapid growth of social commerce sites such as Coupang and Ticket Monster, it is very important to understand the user's purchase decision-making process in a social commerce environment. The purpose of this study is to develop a richer understanding of the goals of users using social commerce. Second, a methodological alternative for analyzing the user's goals is introduced. In this study, laddering interview and means-end chain analysis were used. As a result of interview conducted on 40 users who have more than 6 months of purchasing experience using social commerce, a hierarchical goal map showing the user's goal structure was derived. This map contains 22 ultimate goals of social commerce, including warm relationships with others, fun and enjoyment of shopping, accomplishment, satisfaction, financial saving, and convenience. In addition, there are various paths from activities to ultimate goals, so investigating the goals pursued by users can give us insight into understanding user.

• Archives of Plastic Surgery
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• v.49 no.5
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• pp.614-616
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• 2022

As of November 2021, TikTok has one billion monthly active users and is recognized as the most engaging social media platform. TikTok has seen a surge in users and content creators, ranging from athletes to medical professionals. In the past year, content creators have utilized the app to advocate for social reforms, education, and other uses that were not previously considered. Breast cancer is the most commonly diagnosed cancer in women, with an expected 281,550 new cases of invasive breast cancer in 2021. As more individuals with breast cancer choose to undergo resection, the demand for autologous fat grafting in breast reconstruction has increased due to the natural look and feel of breast tissue. The purpose of this article is to analyze content related to breast reconstruction with fat grafting found on TikTok and recommend methods to improve patient education, care, and outcomes. We searched TikTok on November 1, 2021, for videos using the phrase "breast reconstruction with fat grafting." The top 200 videos retrieved from the TikTok search algorithm were analyzed, and all commentaries, duplicates, and nonrelevant videos were removed. Video characteristics were collected, and two independent reviewers generated a DISCERN score A total of 131 videos were included in the study. They were found to have a combined 1,871,980 likes, 41,113 comments, and 58,662 shares. The videos had an average DISCERN score of 2.16. Content creators had an overall low DISCERN score in items involving the use of references, disclosure of risks for not obtaining treatment, and support for shared decision-making. When stratified, the DISCERN score was higher for videos created by physicians (DISCERN average 2.48) than for videos created by nonphysicians (DISCERN average 1.99; p < 0.001).