• The Journal of Information Systems
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• v.22 no.2
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• pp.25-49
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• 2013

By virtue of the development and widespread of social network services, the importance of SNS for an individual's social capital formation as well as people's act of sharing information is increasingly highlighted. However, there are still few empirical studies on successful formation of SNS, people's attitude towards participation in SNS, and the brisk act of sharing information in the SNS as yet. This study performed an analysis that, in terms of forming the successful SNS, people's attachment to the group in SNS induces the attitude towards the participation in SNS, and the information-sharing act on the basis of the socio-psychological theory. For this purpose, this study carried out empirical study by dividing the influential factors into the attachment to online group, and attachment to the members in SNS group on the basis of trust. This study set up the component factors in trust as high-dimensional factors, and used SPSS 18.0 and SmartPLS 2.0 as analysis tools. Analysis results confirmed that group formation in SNS and people's attachment to the group were significantly influence attitude towards participation in SNS as well as information sharing behavior. This result implies that group formation in SNS plays an important role in active use of SNS.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.294-306
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• 2005

Group oriented multicast applications are becoming increasingly popular in mobile ad hoc networks (MANETs). Due to dynamic topology of MANETs, stateless multicast protocols are finding increased acceptance since they do not require maintenance of state information at intermediate nodes. Recently, several multicast schemes have been proposed which scale better' with the number of multicast sessions than traditional multicast strategies. These schemes are also known as explicit multicast (Xcast; explicit list of destinations in the packet header) or small group multicast (SGM). In this paper, we propose a new scheme for small group' multicast in MANETs named extended explicit multicast (E2M), which is implemented on top of Xcast and introduces mechanisms to make it scalable with number of group members for a given multicast session. Unlike other schemes, E2M does not make any assumptions related to network topology or node location. It is based on the novel concept of dynamic selection of Xcast forwarders (XFs) between a source and its potential destinations. The XF selection is based on group membership and the processing overhead involved in supporting the Xcast protocol at a given node. If the number of members in a given session is small, E2M behaves just like the basic Xcast scheme with no intermediate XFs. As group membership increases, nodes may dynamically decide to become an XF. This scheme, which can work with few E2M aware nodes in the network, provides transparency of stateless multicast, reduces header processing overhead, minimizes Xcast control traffic, and makes Xcast scalable with the number of group members.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3678-3698
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• 2017

With the rapid development of vehicular ad hoc Network (VANET), it has gained significant popularity and received increasing attentions from both academics and industry communities in aspects of security and efficiency. To address the security and efficiency issues, a self-authentication and deniable efficient group key agreement protocol is proposed in this paper. The scheme establishes a group between road side units (RSUs) and vehicles by using self-authentication without certification authority, and improves certification efficiency by using group key (GK) transmission method. At the same time, to avoid the attacker attacking the legal vehicle by RSUs, we adopt deniable group key agreement method to negotiation session key (sk) and use it to transmit GK between RSUs. In addition, vehicles not only broadcast messages to other vehicles, but also communicate with other members in the same group. Therefore, group communication is necessary in VANET. Finally, the performance analysis shows superiority of our scheme in security problems, meanwhile the verification delay, transmission overheard and message delay get significant improvement than other related schemes.

• Child Health Nursing Research
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• v.29 no.2
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• pp.128-136
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• 2023

Purpose: This study aimed to identify the main keywords and research topics used in research on problematic smartphone use (PSU) among children (6-12 years old), including parental factors. Methods: The publication period for the literature was set from January 2007 to January 2022, as smartphones were first released in 2007. In total, 395 articles were identified, 230 of which were included in the final analysis. Text network analysis was performed using NetMiner 4.5. Results: Research on this topic has steadily increased since 2007, with 40 papers published in 2021. Eight main research topics were derived: group 1, parental attitudes; group 2, children's PSU behavior and parental support; group 3, family environment and behavioral addiction; group 4, social relationships; group 5, seeking solutions; group 6, parent-child relationships; group 7, children's mental health and school adaptation; and group 8, PSU in adolescents. Conclusion: Parental factors related to PSU have been studied in various aspects. However, more active research on school-age children's PSU needs to be conducted due to the paucity of research in this population compared to studies conducted among adolescents. The results of this study provide useful data for selecting research topics in the field of PSU.

• Proceedings of the Korea Database Society Conference
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• 1999.06a
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products me classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem far disposal products. In this paper, a heuristic approach fuzzy ART neural network is suggested. The modified fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its ai is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.03a
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• pp.253-260
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• 1999

The recycling cell formation problem means that disposal products are classified into recycling part families using group technology in their end of life phase. Disposal products have the uncertainties of product status by usage influences during product use phase and recycling cells are formed design, process and usage attributes. In order to treat the uncertainties, fuzzy set theory and fuzzy logic-based neural network model are applied to recycling cell formation problem for disposal products. In this paper, a heuristic approach for fuzzy ART neural network is suggested. The modified Fuzzy ART neural network is shown that it has a great efficiency and give an extension for systematically generating alternative solutions in the recycling cell formation problem. We present the results of this approach applied to disposal refrigerators and the comparison of performances between other algorithms. This paper introduced a procedure which integrates economic and environmental factors into the disassembly of disposal products for recycling in recycling cells. A qualitative method of disassembly analysis is developed and its aim is to improve the efficiency of the disassembly and to generated an optimal disassembly which maximize profits and minimize environmental impact. Three criteria established to reduce the search space and facilitate recycling opportunities.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.5
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• pp.727-734
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• 1997

In practice, the design of forging processes is performed based on an experience-oriented technology, that is designer's experience and expensive trial and errors. Using the finite element simulation and the artificial neural network, we propose an optimal die geometry satisfying the design conditions of final product. A three-layer neural network is used and the back propagation algorithm is employed to train the network. An optimal die geometry that satisfied the same between inner extruded rib and outer extruded one is determined by applying the ability of function approximation of neural network. The neural networks may reduce the number of finite element simulation for determine the optimal die geometry of forging products and further they are usefully applied to physical modelling for the forging design.

• Journal of Korean Society of Rural Planning
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• v.23 no.3
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• pp.1-12
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• 2017

The purpose of this study is to reveal network potential among agricultural villages focused on landscape and amenity resources. For this study, we conducted Social Network Analysis (SNA) utilizing existing landscape resource database. As a result of the study, major landscape types shared among villages were found for each city. For example, agricultural and residential landscapes were identified as major types for Danjin city. Add to major landscape resources, in Dangjin city, Habduk village were recognized as a core. Seokmun, Daehoji, Woogang, and Sunseong villages were widely found as the sub core group. For Seosan city, Jigok, Palbong, and Kobuk villages were widely recognized as core group. Most of villages which indicated the highest degree centrality were superior in terms of the number of total landscape resources as well as landscape type diversity. These results can be useful for initial planning process when considering major theme for landscape-based network organization. Also, this information will be helpful for planning stage through the specification of the potential role of each village in overall network.

• Journal of Positioning, Navigation, and Timing
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• v.13 no.1
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• pp.103-110
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• 2024

In this paper, a test bed for real-time network Real-Time Kinematic (RTK) research was constructed using reference stations of the NGII. A group of candidate station networks was derived, including three stations in Seoul. The group consisted of four stations with a distance of less than 100 km between them. Among several candidates, a network composed of stations with short distances between them and demonstrating good data quality for all reference stations was selected as the test bed. After collecting real-time data in Radio Technical Committee for Maritime services (RTCM) format from the selected stations and conducting a noise analysis on measurements, mm-level carrier phase measurement noise was confirmed. Afterwards, the user set the reference station inside the test bed and analyzed the network RTK positioning performance of the MAC method using the GPS L1 frequency as post-processing. From the result of the analysis it was confirmed that the residual error for all users was within 10 cm after applying the correction. Additionally, after determining integer ambiguities through Least-squares AMBiguity Decorrelation Adjustment (LAMBDA), it was confirmed that the fix rate was 100%, and all ambiguities were resolved as true values.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.67-79
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• 2023

In the image field, data augmentation refers to increasing the amount of data through an editing method such as rotating or cropping a photo. In this study, a generative adversarial network (GAN) image was created using CycleGAN, and various colors of dogs were reflected through data augmentation. In particular, dog data from the Stanford Dogs Dataset and Oxford-IIIT Pet Dataset were used, and 10 breeds of dog, corresponding to 300 images each, were selected. Subsequently, a GAN image was generated using CycleGAN, and four learning groups were established: 2,000 original photos (group I); 2,000 original photos + 1,000 GAN images (group II); 3,000 original photos (group III); and 3,000 original photos + 1,000 GAN images (group IV). The amount of data in each learning group was augmented using existing data augmentation methods such as rotating, cropping, erasing, and distorting. The augmented photo data were used to train the MobileNet_v3_Large, ResNet-152, InceptionResNet_v2, and NASNet_Large frameworks to evaluate the classification accuracy and loss. The top-3 accuracy for each deep neural network model was as follows: MobileNet_v3_Large of 86.4% (group I), 85.4% (group II), 90.4% (group III), and 89.2% (group IV); ResNet-152 of 82.4% (group I), 83.7% (group II), 84.7% (group III), and 84.9% (group IV); InceptionResNet_v2 of 90.7% (group I), 88.4% (group II), 93.3% (group III), and 93.1% (group IV); and NASNet_Large of 85% (group I), 88.1% (group II), 91.8% (group III), and 92% (group IV). The InceptionResNet_v2 model exhibited the highest image classification accuracy, and the NASNet_Large model exhibited the highest increase in the accuracy owing to data augmentation.