• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.714-721
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• 2020

DNN is expanding its use in embedded systems such as robots and autonomous vehicles. For high recognition accuracy, computational complexity is greatly increased, and multiple DNNs are running aperiodically. Therefore, the ability processing multiple DNNs in embedded environments is a crucial issue. Accordingly, multicore based platforms are being released. However, most DNN models are operated in a batch process, and when multiple DNNs are operated in multicore together, the execution time deviation between each DNN may be large and the end-to-end execution time of the whole DNNs could be long depending on how they are allocated to the cores. In this paper, we solve these problems by providing a framework that decompose each DNN into individual layers and then distribute to multicores through a global queue. As a result of the experiment, the total DNN execution time was reduced by 31%, and when operating multiple identical DNNs, the deviation in execution time was reduced by up to 95.1%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.616-622
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• 2020

Recently, as the interest in power saving increases with the development of IoT technology, research on power saving of smart devices, which are being miniaturized, is being actively conducted. In particular, due to the diversification of IoT-based smart devices and the increase in personal penetration rate, the issue of standby power even when not in use is increasing. However, there is a drawback of physically unplugging the outlet or turning off the power in order to substantially reduce standby power. Since Zigbee is used instead of the existing IP, it is necessary to change to the IoT standard protocol based on the Internet network. Therefore, this paper designed and implemented the standby power saving system applying CoAP, the IoT standard protocol, to the existing Zigbee technology. Existing systems and evaluations confirmed that the average standby power of about 8.4Wh was reduced.

• Journal of the Korean Society of Earth Science Education
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• v.13 no.3
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• pp.330-343
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• 2020

In this study, STEAM program on the subject of 'atmospheric circulation and surface current' was produced based on data and applied to 106 first-year high school students to analyze its effect and problem-solving processes. This program was organized to collect, refine, visualize, and analyze data and to allow communication processes to proceed based on these results. Using this, the concept of circulation in daily life was expanded from a global perspective to identify problems about circulation around the world. As a result of the application of the program, significant changes were identified in knowledge information processing competency. Also, significant changes were made in terms of convergence and creativity, which are sub categories among STEAM core competencies. It also sought to obtain suggestions for data-based STEAM education by analyzing students' responses in the form of a Text network.

• Parasites, Hosts and Diseases
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• v.58 no.5
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• pp.513-525
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• 2020

Clonorchis sinensis is a food-borne trematode that infects more than 15 million people. The liver fluke causes clonorchiasis and chronical cholangitis, and promotes cholangiocarcinoma. The underlying molecular pathogenesis occurring in the bile duct by the infection is little known. In this study, transcriptome profile in the bile ducts infected with C. sinensis were analyzed using microarray methods. Differentially expressed genes (DEGs) were 1,563 and 1,457 at 2 and 4 weeks after infection. Majority of the DEGs were temporally dysregulated at 2 weeks, but 519 DEGs showed monotonically changing expression patterns that formed seven distinct expression profiles. Protein-protein interaction (PPI) analysis of the DEG products revealed 5 sub-networks and 10 key hub proteins while weighted co-expression network analysis (WGCNA)-derived gene-gene interaction exhibited 16 co-expression modules and 13 key hub genes. The DEGs were significantly enriched in 16 Kyoto Encyclopedia of Genes and Genomes pathways, which were related to original systems, cellular process, environmental information processing, and human diseases. This study uncovered a global picture of gene expression profiles in the bile ducts infected with C. sinensis, and provided a set of potent predictive biomarkers for early diagnosis of clonorchiasis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.361-367
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• 2021

Information search in video streaming services such as YouTube is replacing traditional information search services. To find desired detailed information in such a video, users should repeatedly navigate several points in the video, resulting in a waste of time and network traffic. In this paper, we propose a method to assist users in searching for information in a video by using DBSCAN clustering and LSTM. Our LSTM model is trained with a dataset that consists of user search sequences and their final target points categorized by DBSCAN clustering algorithm. Then, our proposed method utilizes the trained model to suggest an expected category for the user's desired target point based on a partial search sequence that can be collected at the beginning of the search. Our experiment results show that the proposed method successfully finds user destination points with 98% accuracy and 7s of the time difference by average.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.433-438
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• 2021

This study investigates the relationship between lexical sophistication features and English proficiency for Korean college students. Essays from the ICNALE(International Corpus Network of Asian Learners of English) corpus were analyzed, using TAALES program. In order to examine whether or not there are statistically significant differences in lexical sophistication features across three groups, MANOVA was conducted. Results showed that the lexical sophistication features were significantly affected by English proficiency level. Essays written by Korean students with different English proficiency levels can be differentiated in terms of various lexical sophistication features including content words frequency, content words familiarity, lexical decision mean reaction time function words, hypernymy verbs, word naming response time function words, age of acquisition content words.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.284-291
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• 2021

In this paper, we study the consensus problem for multi-agent systems with input saturations. The goal of consensus is to achieve a swarming behavior of multi-agent systems by reaching the agreement through information exchange. This paper considers agents modeled by first-order dynamics with input saturations. In order to guarantee the global convergence of the agents, it is assumed that the agents are stable. Moreover, considering the disturbances, we propose the PI based duplex control method to achieve the consensus. The proposed P controller and I controller are composed of different information network. Then, we investigate the conditions of the information networks and the control gains of P, I controllers to achieve the consensus applying the Lyapunov stability theorem and the Lasalle's Invariance Principle. Finally, we conduct the simulations to validate the theoretical results.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.571-576
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• 2021

This study was carried out to overcome the problems of the existing fitness business and to build a fitness system that can meet the increased demand in the Corona situation. As a platform technology for non-face-to-face fitness edutainment service, it is a next-generation fitness exercise device that can use various body parts and synchronize network-type information. By synchronizing the exercise information of the fitness equipment, it was composed of learning contents through MR-based avatars. A quantified result was derived from examining the applicability of the customized evaluation system through momentum analysis with A.I analysis applying the LSTM-based algorithm according to the cumulative exercise effect of the user. It is a motion capture and 3D visualization fitness program for the application of systematic exercise techniques through academic experts, and it is judged that it will contribute to the improvement of the user's fitness knowledge and exercise ability.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.475-480
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• 2021

With the rapid development of mobile, cloud computing technology and social network services, we are in the flood of huge data and realize that these large-scale data contain very precious value and important information. Big data, however, have both latent useful value and critical risks, so, nowadays, a lot of researches and applications for big data has been executed actively in order to extract useful information from big data efficiently and make the most of the potential information effectively. At this moment, the data analysis technique that can extract precious information from big data efficiently is the most important step in big data computing process. In this study, we investigate various data analysis techniques that can extract the most useful information in big data computing process efficiently, compare pros and cons of those techniques, and propose proper data analysis method that can help us to find out the best solution of the big data analysis in the peculiar situation.

• Journal of Digital Convergence
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• v.20 no.4
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• pp.133-145
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• 2022

As a result of the study, the poorest keywords were information, big data, management, policy, government, law, and smart. In addition, as a result of network analysis, related research was being conducted on topics such as data industry policy, data governance performance, defense, governance, and data public. The four topics derived through topic modeling were "DG policy," "DG platform," "DG in laws," and "DG implementation," of which research related to "DG platform" showed an increasing trend, and "DG implementation" tended to shrink. This study comprehensively summarized data governance-related studies. Data governance needs to expand research areas from various perspectives and related fields such as data management and data integration policies at the organizational level, and related technologies. In the future, we can expand the analysis targets for overseas data governance and expect follow-up studies on research directions and policy directions in industries that require data-based future industries such as Industry 4.0, artificial intelligence, and Metaverse.