• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.3B
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• pp.408-420
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• 2010

On a Mobile Ad hoc NETwork(MANET), it is difficult to detect and prevent misbehaviors nodes existing between end nodes, as communication between remote nodes is made through multiple hop routes due to lack of a fixed networked structure. Therefore, to maintain MANET's performance and security, a technique to identify misbehaving middle nodes and nodes that are compromise by such nodes is required. However, previously proposed techniques assumed that nodes comprising MANET are in a friendly and cooperative relationship, and suggested only methods to identify misbehaving nodes. When these methods are applied to a larger-scale MANET, large overhead is induced. As such, this paper suggests a system model called Secure Cluster-based MANET(SecCBM) to provide secure communication between components aperANET and to ensure eed. As such, this pand managems suapemisbehavior nodes. SecCBM consists apetwo stages. The first is the preventis pstage, whereemisbehavior nodes are identified when rANET is comprised by using a cluster-based hierarchical control structure through dynamic authentication. The second is the post-preventis pstage, whereemisbehavior nodes created during the course apecommunication amongst nodes comprising the network are dh, thed by using FC and MN tables. Through this, MANET's communication safety and efficiency were improved and the proposed method was confirmed to be suitable for MANET through simulation performance evaluation.

• Journal of Convergence for Information Technology
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• v.7 no.4
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• pp.105-111
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• 2017

With the emergence of the fourth industrial revolution, more and more attempts have been made to apply IoT technology to the manufacturing process and launch the product. In this paper, we propose IoT authentication scheme based on hash chain which can easily apply IoT device to small and medium enterprises in Korea. In the proposed method, the companies that installed IoT devices suitable for the manufacturing environment are selected to maintain the linkage between IoT devices so that product information and release information can be efficiently collected and managed during the entire manufacturing process. In addition, the proposed scheme is characterized in that it does not require an additional encryption / decryption algorithm because the authentication information of the IoT device is constructed based on a hash chain. As a result of the performance evaluation, the efficiency of the manufacturing process was improved by 18.5% and the processing of the manufacturing process with the IoT device was shortened by 20.1% on the average according to the application of the IoT device. In addition, the labor cost reduction costs in the manufacturing process decreased by an average of 30.7%.

• Journal of Korean Home Economics Education Association
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• v.32 no.1
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• pp.51-76
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• 2020

The purpose of this research was to develop the education program on traditional living culture for home economics(HE) based on the 2015 revised national curriculum. The existing school curriculum for traditional living culture tends to overly focus on the theories about traditional culture and suffer from absence of continuity in learning activities. It can be argued that HE is an ideal subject for dealing with traditional living culture as it aims to develop students' ability to recreate the traditional culture, meeting present needs and trends. This study, thus, attempted to present the practical ways of improving the quality of education on traditional living culture by developing HE education program for high school students. To fulfill the purpose, this research, as a teaching topic, selected the traditional patterns and the "Obangsaek"(Korean traditional five colors) which can commonly be dealt with in the subjects of traditional Korean food, Korean costume and Korean style house. In particular, the program was developed following the ADDE process. In the stage of analysis, this article analyzed the HE curriculum and making activities included in HE textbooks based on the 2015 revised national curriculum, as well as the needs of teachers and students regarding traditional living culture education. In the stage of design, this study developed the instructional model, selecting class topics, tools and materials. In the stage of development, the programs on traditional living culture including costume, food and house were developed. In the evaluation phase, this research conducted the validity test and received the feedbacks from 12 HE educators in order to complete the programs. This study finally suggested that future studies in this area examine the effect of the presented programs on enhancing the students' perception of traditional culture and the will of developing and succeeding the traditional living culture.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.2
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• pp.165-172
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• 2010

In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.

• Journal of Biomedical Engineering Research
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• v.35 no.5
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• pp.160-168
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• 2014

Continuous body temperature monitoring is useful and essential in diverse medical procedures such as infection onset detection, therapeutic hypothermia, circadian rhythm monitoring, sleep disorder assessment, and gynecological research. However, the existing thermometers are too invasive or intrusive to be applied to long-term body temperature monitoring. In our previous study, we invented the bi-medium deep body thermometer which can noninvasively and continuously monitor deep tissue temperature. And the ratio of thermal resistances expressed as K-value should be obtained to estimate body temperature with the thermometer and it can be different under various measurement environments. Although the device was proven to be useful through preliminary simulation test and small group of human study, the experimental environment was restrictive in our previous approach. In this study, a finite element simulation was executed to obtain the K-value and evaluate the accuracy of bi-medium thermometer under various measurement environments. In addition, K-value estimation equation was developed by analyzing the influence of 5 measurement environmental factors (medium length, medium height, tissue depth, blood perfusion rate, and ambient temperature) on K-value. The results revealed that the estimation accuracy of bi-medium deep body thermometer based on computer simulation was very high (RMSE < $0.003^{\circ}C$) in various measurement environments. Also, bi-medium deep body thermometer based on K-value estimation equation showed relatively accurate results (RMSE < $0.3^{\circ}C$) except for one case. Although the K-value estimation technology should be improved for more accurate body temperature estimation, the results of finite element simulation showed that bi-medium deep body thermometer could accurately measure various tissue temperatures under diverse environments.

• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.61-69
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• 2019

In this paper, we propose a multisensory(i.e., visual-auditory-tactile) based AR system for the education of cultural heritage. The proposed system provides a multisensory interaction by designing a user to experience with a 3D printed artifact which is mapped by a virtual 3D content of digital heritage. Compared with the existing systems of cultural heritage education based on augmented reality(AR) technology, this system focused on not only providing learning experience via a sense of visual and auditory, but also a sense of tactile. Furthermore, since this systems mainly provided the direct interactions using a 3D printed model, it gives a higher degree of realism than existing system that use touch or click motions on a 2D display of mobile phones and tablets. According to a result of user testing, we concluded that the proposed system delivered the excellent presence and learning flow to users. Particularly, from the usability evaluation, a 3D printed target artifact which is similar in shape to original heritage artifact, achieved the highest scores among the various tested targets.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.611-620
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• 2020

The purpose of the study is to find creativity factors of students in the process of small group modeling and relate them to the types of interactions among students. In order to capture students' detailed interactions, this study was conducted as an 'essential case study' through qualitative analysis. We have developed the modules of nine lessons about terraforming, and they were used in an actual classroom. In order to understand the creativity of the students in the process of modeling, students' discourses and interview data were analyzed using 19 creative factors or abilities. The findings are as follows. Frequently found creativity factors are Elaboration, Evaluation, Visualization, Resist premature closer, Originality, Analysis and Concentration. And students' interactions that affect students' creativity in the process of modeling can be classified into four categories: Suggestion, Agreement, Questioning, Refutation, and Conversion. Through each interaction, students demonstrated the process of expressing and modifying their own thoughts and ideas in the modeling process. The findings of the study suggest that it is important to the teachers to understand types of interactions among students and the relationship between the types of interaction and creativity factors for students' creative modeling in modeling-based learning.

• Journal of Music and Human Behavior
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• v.18 no.1
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• pp.79-102
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• 2021

The purpose of this study was to identify the teaching methods used in inclusive music classes at elementary schools by of music in elementary school inclusive classes through the application of understanding by design and differentiated instruction, and to explore the feasibility of inclusive education. To this end, based on the 2.0 version of the backward design template, a unit for music lessons for 3rd and 4th grade inclusive classes was developed. The unit presented elements of differentiated instruction that considered students with intellectual disabilities at each stage. In the first stage, goals and essential questions were presented by analyzing the curriculum's achievement standards. In the second stage, a performance task was developed using the GRASPS technique, guidelines and examples were presented. Various evaluation methods based on students' readiness, interest, and learning type were suggested. In the third stage, the unit's seven lessons were planned using the WHERETO model. Examples of differentiated instruction for students with intellectual disabilities were presented by flexibly using classroom elements. This study indicated that understanding by design and differentiated instruction can be applied to inclusive education. Future studies on more diversified educational design and strategies are needed for promoting inclusive education.

• Korean Journal of Ecology and Environment
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• v.53 no.4
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• pp.311-323
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• 2020

We analyzed food sources of 45 fish species in 28 genera of 12 families based on literature data in freshwater ecosystems of South Korea. The food sources of 45 fish species included in a total of 26 phyla, 42 classes, 94 orders, 189 families and 294 genera. Among them, animal food sources were 16 phyla, 24 classes, 54 orders, 126 families and 212 genera, whereas plant food sources were relatively small with 10 phyla, 18 classes, 42 orders, 63 families and 82 genera. The animal food sources were classified into Arthropod, Insecta, Diptera and Chironomidae according to taxa. Meanwhile, Bacillariophyta, Bacillariophyceae, Cymbellales and Cymbellaceae were the most abundant among the plant sources. Self-Organized Map (SOM) and network analysis were conducted the food sources were classified into taxonomic groups and the feeding types of fish : 45 fish species were divided into five groups, characterizing 1) fishvores, 2) invertebratevores, planktivores including 3) zooplankton and 4) phytoplankton, and 5) omnivores. The network analysis presented link association between fishes and food sources. Macroinvertebrate including diptera and ephemeroptera were revealed as hub food sources based on network analysis. This literature study would expect that the application model with the food source of fish could be utilized for the evaluation of the food network or chain in freshwater ecosystems.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.751-760
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• 2021

Most bridges in Korea are over 20 years old, and many problems linked to their deterioration are being reported. The current practice for bridge inspection mainly depends on expert evaluation, which can be subjective. Recent studies have introduced data-driven methods using building information modeling, which can be more efficient and objective, but these methods require manual procedures that consume time and money. To overcome this, this study developed an image-based automaticbridge component classification network to reduce the time and cost required for converting the visual information of bridges to a digital model. The proposed method comprises two convolutional neural networks. The first network estimates the type of the bridge based on the superstructure, and the second network classifies the bridge components. In avalidation test, the proposed system automatically classified the components of 461 bridge images with 96.6 % of accuracy. The proposed approach is expected to contribute toward current bridge maintenance practice.