• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.1-8
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• 2013

Data mining techniques are used to find important and meaningful information from huge databases, and pattern mining is one of the significant data mining techniques. Pattern mining is a method of discovering useful patterns from the huge databases. Frequent pattern mining which is one of the pattern mining extracts patterns having higher frequencies than a minimum support threshold from databases, and the patterns are called frequent patterns. Traditional frequent pattern mining is based on a single minimum support threshold for the whole database to perform mining frequent patterns. This single support model implicitly supposes that all of the items in the database have the same nature. In real world applications, however, each item in databases can have relative characteristics, and thus an appropriate pattern mining technique which reflects the characteristics is required. In the framework of frequent pattern mining, where the natures of items are not considered, it needs to set the single minimum support threshold to a too low value for mining patterns containing rare items. It leads to too many patterns including meaningless items though. In contrast, we cannot mine any pattern if a too high threshold is used. This dilemma is called the rare item problem. To solve this problem, the initial researches proposed approximate approaches which split data into several groups according to item frequencies or group related rare items. However, these methods cannot find all of the frequent patterns including rare frequent patterns due to being based on approximate techniques. Hence, pattern mining model with multiple minimum supports is proposed in order to solve the rare item problem. In the model, each item has a corresponding minimum support threshold, called MIS (Minimum Item Support), and it is calculated based on item frequencies in databases. The multiple minimum supports model finds all of the rare frequent patterns without generating meaningless patterns and losing significant patterns by applying the MIS. Meanwhile, candidate patterns are extracted during a process of mining frequent patterns, and the only single minimum support is compared with frequencies of the candidate patterns in the single minimum support model. Therefore, the characteristics of items consist of the candidate patterns are not reflected. In addition, the rare item problem occurs in the model. In order to address this issue in the multiple minimum supports model, the minimum MIS value among all of the values of items in a candidate pattern is used as a minimum support threshold with respect to the candidate pattern for considering its characteristics. For efficiently mining frequent patterns including rare frequent patterns by adopting the above concept, tree based algorithms of the multiple minimum supports model sort items in a tree according to MIS descending order in contrast to those of the single minimum support model, where the items are ordered in frequency descending order. In this paper, we study the characteristics of the frequent pattern mining based on multiple minimum supports and conduct performance evaluation with a general frequent pattern mining algorithm in terms of runtime, memory usage, and scalability. Experimental results show that the multiple minimum supports based algorithm outperforms the single minimum support based one and demands more memory usage for MIS information. Moreover, the compared algorithms have a good scalability in the results.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.55-60
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• 2020

In this paper, we propose an access control system using cryptography as a method to protect personal data in public blockchain. The proposed system is designed to encrypt data according to the access policy, store it in the blockchain, and decrypt only the person who satisfy the access policy. In order to improve performance and scalability, an encryption mechanism is implemented outside the blockchain. Therefore, data access performance could be preserved while cryptographic operations executed Furthermore it can also improve the scalability by adding new access control modules while preserving the current configuration of blockchain network. The encryption scheme is based on the attribute-based encryption (ABE). However, unlike the traditional ABE, the "retention period", is incorporated into the access structure to ensure the right to be forgotten. In addition, symmetric key cryptograpic algorithms are used for the performance of ABE. We implemented the proposed system in a public blockchain and conducted the performance evaluation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.12A
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• pp.1238-1245
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• 2006

Interest to the RTLS that is one of RFID applications is increasing in recent. The RTLS(Real Time Locating Systems) is one of applications for locating and tracking using RFID tags which are attached to something like container, pallet, or all the things. This paper presents the design and the implementation of an RTLS system using 433MHz active RFID tags and use radio frequency to provide the scalability. Our system we developed using RFID platform takes into account an RTLS standard. Also, in this paper a routing protocol is included to data delivery to server via each reader. In order to perform the evaluation, in addition, some experiments in out door are performed and results such as error metric and distance are also included. Furthermore, simulation for the routing protocol we supposed is also included.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.12A
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• pp.964-974
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• 2003

With increasing use of a personal mobile computer. the Mobile IPv6 is one of the main protocols that support mobility and complies with IPv6 specification. Similar to the mobile IPv6, the mobile IPv6 also has limitations on fast moving condition. The Hierarchical Mobile IPv6 is a solution that overcomes these limitations. The Hierarchical Mobile IPv6 is a micro mobility protocol that supports fast mobile IP handover and reduces signaling overhead with Mobility Anchor Point(MAP). But until now no paging method is applied to the Hierarchical Mobile IPv6 to reduce unnecessary signaling overhead and power consumption of mobile nodes. So, the paging mechanism for the Hierarchical Mobile IPv6 is proposed in this paper. the mechanism is implemented by making use of the destination option header and extension function and the last location algorithm. The results show that the Hierarchical Mobile IPv6 with the paging ability reduces the traffic of mobile networks by removing unnecessary binding update packet generated whenever handover takes place. Also, the larger the paging size is. the less the number of BU(Binding Update) massage generated.

• Journal of the Korea Society for Simulation
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• v.16 no.3
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• pp.11-18
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• 2007

Recently, as weapon systems have been more diverse and complicated, the factors of risk increase in development. Consequently, demanding reduction of acquired costs and period increase. Under the acquisition environment, more efficiently to develop weapon system, the necessity of application of defense M&S from requirement phase is on the rise. As the importance of M&S is stressed under distributed environment, so the standard of M&S(HLA, SEDRIS, etc.) and the system engineering process, namely FEDEP(Federation Development & Execution Process) have been developed. In this paper using the 5 phase expression, we constructed underwater engagement simulation(UNES) that prototype to develop naval weapon system test bed which take up integrated architecture in HLA. we developed simulators according to FEDEP for expandability and described process applying FEDEP fur UNES development.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.220-223
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• 2016

Explosive growth of smartphone-based mobile nodes has increased exponentially the mobile data traffic on the Internet. To reduce the traffic load on the network and to support the seamless mobility of the mobile nodes, the IETF and 3GPP have standardized a number of mobility management mechanisms. More recently, they are making an effort to find some schemes to distribute the networking systems that involve in the mobility management in order to assure the scalability and the reliability of the network. In IETF, DMM concept for the distributed mobility management on the Internet is being discussed. Specifically, the DMM can be classified into the partially distributed management and fully distributed management. In this paper, we propose a fully distributed mobility management scheme (FuDMM) on PMIPv6-based network by applying the extended NDP. We also present the performance of FuDMM using the comparative analysis with the existing ones.

• Journal of The Korean Association For Science Education
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• v.44 no.1
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• pp.39-55
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• 2024

This study aimed to examine research trends related to Natural Language Processing (NLP) in science education by analyzing 37 domestic and international documents that utilized NLP techniques in the field of science education from 2011 to September 2023. In particular, the study systematically analyzed the content, focusing on the main application areas of NLP techniques in science education, the role of teachers when utilizing NLP techniques, and a comparison of domestic and international perspectives. The analysis results are as follows: Firstly, it was confirmed that NLP techniques are significantly utilized in formative assessment, automatic scoring, literature review and classification, and pattern extraction in science education. Utilizing NLP in formative assessment allows for real-time analysis of students' learning processes and comprehension, reducing the burden on teachers' lessons and providing accurate, effective feedback to students. In automatic scoring, it contributes to the rapid and precise evaluation of students' responses. In literature review and classification using NLP, it helps to effectively analyze the topics and trends of research related to science education and student reports. It also helps to set future research directions. Utilizing NLP techniques in pattern extraction allows for effective analysis of commonalities or patterns in students' thoughts and responses. Secondly, the introduction of NLP techniques in science education has expanded the role of teachers from mere transmitters of knowledge to leaders who support and facilitate students' learning, requiring teachers to continuously develop their expertise. Thirdly, as domestic research on NLP is focused on literature review and classification, it is necessary to create an environment conducive to the easy collection of text data to diversify NLP research in Korea. Based on these analysis results, the study discussed ways to utilize NLP techniques in science education.

• KIISE Transactions on Computing Practices
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• v.24 no.1
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• pp.53-57
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• 2018

A poisoning accident is often caused by a situation in which people eat poisonous mushrooms because they cannot distinguish between edible mushrooms and poisonous mushrooms. In this paper, we propose an automatic mushroom recognition system by using the convolutional neural network. We collected 1478 mushroom images of 38 species using image crawling, and used the dataset for learning the convolutional neural network. A comparison experiment using AlexNet, VGGNet, and GoogLeNet was performed using the collected datasets, and a comparison experiment using a class number expansion and a fine-tuning technique for transfer learning were performed. As a result of our experiment, we achieve 82.63% top-1 accuracy and 96.84% top-5 accuracy on test set of our dataset.

• Journal of Internet Computing and Services
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• v.12 no.4
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• pp.107-117
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• 2011

The appearance of Web has brought an substantial revolution to all fields of society such knowledge management and business transaction as well as traditional information retrieval. In this paper, we propose an EFASIT(Extended Fuzzy AHP and SImilarity Technology) model considering the emotion analysis. And we combine the Extended Fuzzy AHP Method(EFAM) with SImilarity Technology(SIT) based on the domain corpus information in order to efficiently retrieve the document on the Web. The proposed the EFASIT model can generate the more definite rule according to integration of fuzzy knowledge of various decision-maker, and can give a help to decision-making, and confirms through the experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.488-494
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• 2013

For the activeness and autonomy of a sensor network, the efficient migration method of a mobile agent and the consistent naming services are the required components of a sensor network. Accordingly, this paper presented the implementation of backward migration of an active rule mobile agent applying the naming method based on RMI that used the meta_table including the informations about the components of a sensor network. This study implemented based on the extension of the forward migration[12], and the results of the various experiments present the efficacy of mobile agent middleware system and the possibility of constructing efficient sensor network application environment. And, the results of this study are able to enhance the adaptability on dynamic changes of environment in sensor network application development.